Hernán Díaz, J. J. Palacios, I. G. Rodríguez, C. R. Vela
In this paper, a novel Artificial Bee Colony algorithm is proposed to solve a variant of the Job Shop Scheduling Problem where only an interval of possible processing times is known for each operation. The solving method incorporates a diversification strategy based on the seasonal behaviour of bees. That is, the bees tend to explore more at the beginning of the search (spring) and be more conservative towards the end (summer to winter). This new strategy helps the algorithm avoid premature convergence, which appeared to be an issue in previous papers tackling the same problem. A thorough parametric analysis is conducted and a comparison of different seasonal models is performed on a set of benchmark instances from the literature. The results illustrate the benefit of using the new strategy, improving the performance of previous ABC-based methods for the same problem. An additional study is conducted to assess the robustness of the solutions obtained under different ranking operators, together with a sensitivity analysis to compare the effect that different levels of uncertainty have on the solutions’ robustness.
{"title":"An elitist seasonal artificial bee colony algorithm for the interval job shop","authors":"Hernán Díaz, J. J. Palacios, I. G. Rodríguez, C. R. Vela","doi":"10.3233/ica-230705","DOIUrl":"https://doi.org/10.3233/ica-230705","url":null,"abstract":"In this paper, a novel Artificial Bee Colony algorithm is proposed to solve a variant of the Job Shop Scheduling Problem where only an interval of possible processing times is known for each operation. The solving method incorporates a diversification strategy based on the seasonal behaviour of bees. That is, the bees tend to explore more at the beginning of the search (spring) and be more conservative towards the end (summer to winter). This new strategy helps the algorithm avoid premature convergence, which appeared to be an issue in previous papers tackling the same problem. A thorough parametric analysis is conducted and a comparison of different seasonal models is performed on a set of benchmark instances from the literature. The results illustrate the benefit of using the new strategy, improving the performance of previous ABC-based methods for the same problem. An additional study is conducted to assess the robustness of the solutions obtained under different ranking operators, together with a sensitivity analysis to compare the effect that different levels of uncertainty have on the solutions’ robustness.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"2015 1","pages":"223-242"},"PeriodicalIF":6.5,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87261805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scheduling is a frequently studied combinatorial optimisation that often needs to be solved under dynamic conditions and to optimise multiple criteria. The most commonly used method for solving dynamic problems are dispatching rules (DRs), simple constructive heuristics that build the schedule incrementally. Since it is difficult to design DRs manually, they are often created automatically using genetic programming. Although such rules work well, their performance is still limited and various methods, especially ensemble learning, are used to improve them. So far, ensembles have only been used in the context of single-objective scheduling problems This study aims to investigate the possibility of constructing ensembles of DRs for solving multi-objective (MO) scheduling problems. To this end, an existing ensemble construction method called SEC is adapted by extending it with non-dominated sorting to construct Pareto fronts of ensembles for a given MO problem. In addition, the algorithms NSGA-II and NSGA-III were adapted to construct ensembles and compared with the SEC method to demonstrate their effectiveness. All methods were evaluated on four MO problems with different number of criteria to be optimised. The results show that ensembles of DRs achieve better Pareto fronts compared to individual DRs. Moreover, the results show that SEC achieves equally good or even slightly better results than NSGA-II and NSGA-III when constructing ensembles, while it is simpler and slightly less computationally expensive. This shows the potential of using ensembles to increase the performance of individual DRs for MO problems.
{"title":"Constructing ensembles of dispatching rules for multi-objective tasks in the unrelated machines environment","authors":"Marko Djurasevic, F. Gil-Gala, D. Jakobović","doi":"10.3233/ica-230704","DOIUrl":"https://doi.org/10.3233/ica-230704","url":null,"abstract":"Scheduling is a frequently studied combinatorial optimisation that often needs to be solved under dynamic conditions and to optimise multiple criteria. The most commonly used method for solving dynamic problems are dispatching rules (DRs), simple constructive heuristics that build the schedule incrementally. Since it is difficult to design DRs manually, they are often created automatically using genetic programming. Although such rules work well, their performance is still limited and various methods, especially ensemble learning, are used to improve them. So far, ensembles have only been used in the context of single-objective scheduling problems This study aims to investigate the possibility of constructing ensembles of DRs for solving multi-objective (MO) scheduling problems. To this end, an existing ensemble construction method called SEC is adapted by extending it with non-dominated sorting to construct Pareto fronts of ensembles for a given MO problem. In addition, the algorithms NSGA-II and NSGA-III were adapted to construct ensembles and compared with the SEC method to demonstrate their effectiveness. All methods were evaluated on four MO problems with different number of criteria to be optimised. The results show that ensembles of DRs achieve better Pareto fronts compared to individual DRs. Moreover, the results show that SEC achieves equally good or even slightly better results than NSGA-II and NSGA-III when constructing ensembles, while it is simpler and slightly less computationally expensive. This shows the potential of using ensembles to increase the performance of individual DRs for MO problems.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"56 1","pages":"275-292"},"PeriodicalIF":6.5,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89039324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Iván García Aguilar, Jorge García-González, Rafael Marcos Luque Baena, Ezequiel López-Rubio, E. Domínguez
The rise of surveillance systems has led to exponential growth in collected data, enabling several advances in Deep Learning to exploit them and automate tasks for autonomous systems. Vehicle detection is a crucial task in the fields of Intelligent Vehicle Systems and Intelligent Transport systems, making it possible to control traffic density or detect accidents and potential risks. This paper presents an optimal meta-method that can be applied to any instant segmentation model, such as Mask R-CNN or YOLACT++. Using the initial detections obtained by these models and super-resolution, an optimized re-inference is performed, allowing the detection of elements not identified a priori and improving the quality of the rest of the detections. The direct application of super-resolution is limited because instance segmentation models process images according to a fixed dimension. Therefore, in cases where the super-resolved images exceed this fixed size, the model will rescale them again, thus losing the desired effect. The advantages of this meta-method lie mainly in the fact that it is not required to modify the model architecture or re-train it. Regardless of the size of the images given as input, super-resolved areas that fit the defined dimension of the object segmentation model will be generated. After applying our proposal, experiments show an improvement of up to 8.1% for the YOLACT++ model used in the Jena sequence of the CityScapes dataset.
{"title":"Optimized instance segmentation by super-resolution and maximal clique generation","authors":"Iván García Aguilar, Jorge García-González, Rafael Marcos Luque Baena, Ezequiel López-Rubio, E. Domínguez","doi":"10.3233/ica-230700","DOIUrl":"https://doi.org/10.3233/ica-230700","url":null,"abstract":"The rise of surveillance systems has led to exponential growth in collected data, enabling several advances in Deep Learning to exploit them and automate tasks for autonomous systems. Vehicle detection is a crucial task in the fields of Intelligent Vehicle Systems and Intelligent Transport systems, making it possible to control traffic density or detect accidents and potential risks. This paper presents an optimal meta-method that can be applied to any instant segmentation model, such as Mask R-CNN or YOLACT++. Using the initial detections obtained by these models and super-resolution, an optimized re-inference is performed, allowing the detection of elements not identified a priori and improving the quality of the rest of the detections. The direct application of super-resolution is limited because instance segmentation models process images according to a fixed dimension. Therefore, in cases where the super-resolved images exceed this fixed size, the model will rescale them again, thus losing the desired effect. The advantages of this meta-method lie mainly in the fact that it is not required to modify the model architecture or re-train it. Regardless of the size of the images given as input, super-resolved areas that fit the defined dimension of the object segmentation model will be generated. After applying our proposal, experiments show an improvement of up to 8.1% for the YOLACT++ model used in the Jena sequence of the CityScapes dataset.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"23 1","pages":"243-256"},"PeriodicalIF":6.5,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87137514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The flexible job shop is a well-known scheduling problem that has historically attracted much research attention both because of its computational complexity and its importance in manufacturing and engineering processes. Here we consider a variant of the problem where uncertainty in operation processing times is modeled using triangular fuzzy numbers. Our objective is to minimize the total energy consumption, which combines the energy required by resources when they are actively processing an operation and the energy consumed by these resources simply for being switched on. To solve this NP-Hard problem, we propose a memetic algorithm, a hybrid metaheuristic method that combines global search with local search. Our focus has been on obtaining an efficient method, capable of obtaining similar solutions quality-wise to the state of the art using a reduced amount of time. To assess the performance of our algorithm, we present an extensive experimental analysis that compares it with previous proposals and evaluates the effect on the search of its different components.
{"title":"Enhanced memetic search for reducing energy consumption in fuzzy flexible job shops","authors":"Pablo García-Gómez, I. G. Rodríguez, C. R. Vela","doi":"10.3233/ica-230699","DOIUrl":"https://doi.org/10.3233/ica-230699","url":null,"abstract":"The flexible job shop is a well-known scheduling problem that has historically attracted much research attention both because of its computational complexity and its importance in manufacturing and engineering processes. Here we consider a variant of the problem where uncertainty in operation processing times is modeled using triangular fuzzy numbers. Our objective is to minimize the total energy consumption, which combines the energy required by resources when they are actively processing an operation and the energy consumed by these resources simply for being switched on. To solve this NP-Hard problem, we propose a memetic algorithm, a hybrid metaheuristic method that combines global search with local search. Our focus has been on obtaining an efficient method, capable of obtaining similar solutions quality-wise to the state of the art using a reduced amount of time. To assess the performance of our algorithm, we present an extensive experimental analysis that compares it with previous proposals and evaluates the effect on the search of its different components.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"58 1","pages":"151-167"},"PeriodicalIF":6.5,"publicationDate":"2023-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74737312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xingyang Liu, Gexiang Zhang, Muhammad Shahid Mastoi, Ferrante Neri, Yang Pu
To guarantee their locomotion, biped robots need to walk stably. The latter is achieved by a high performance in joint control. This article addresses this issue by proposing a novel human-simulated fuzzy (HF) membrane control system of the joint angles. The proposed control system, human-simulated fuzzy membrane controller (HFMC), contains several key elements. The first is an HF algorithm based on human-simulated intelligent control (HSIC). This HF algorithm incorporates elements of both multi-mode proportional-derivative (PD) and fuzzy control, aiming at solving the chattering problem of multi-mode switching while improving control accuracy. The second is a membrane architecture that makes use of the natural parallelisation potential of membrane computing to improve the real-time performance of the controller. The proposed HFMC is utilised as the joint controller for a biped robot. Numerical tests in a simulation are carried out with the planar and slope walking of a five-link biped robot, and the effectiveness of the HFMC is verified by comparing and evaluating the results of the designed HFMC, HSIC and PD. Experimental results demonstrate that the proposed HFMC not only retains the advantages of traditional PD control but also improves control accuracy, real-time performance and stability.
{"title":"A human-simulated fuzzy membrane approach for the joint controller of walking biped robots","authors":"Xingyang Liu, Gexiang Zhang, Muhammad Shahid Mastoi, Ferrante Neri, Yang Pu","doi":"10.3233/ica-230698","DOIUrl":"https://doi.org/10.3233/ica-230698","url":null,"abstract":"To guarantee their locomotion, biped robots need to walk stably. The latter is achieved by a high performance in joint control. This article addresses this issue by proposing a novel human-simulated fuzzy (HF) membrane control system of the joint angles. The proposed control system, human-simulated fuzzy membrane controller (HFMC), contains several key elements. The first is an HF algorithm based on human-simulated intelligent control (HSIC). This HF algorithm incorporates elements of both multi-mode proportional-derivative (PD) and fuzzy control, aiming at solving the chattering problem of multi-mode switching while improving control accuracy. The second is a membrane architecture that makes use of the natural parallelisation potential of membrane computing to improve the real-time performance of the controller. The proposed HFMC is utilised as the joint controller for a biped robot. Numerical tests in a simulation are carried out with the planar and slope walking of a five-link biped robot, and the effectiveness of the HFMC is verified by comparing and evaluating the results of the designed HFMC, HSIC and PD. Experimental results demonstrate that the proposed HFMC not only retains the advantages of traditional PD control but also improves control accuracy, real-time performance and stability.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"24 1","pages":"105-120"},"PeriodicalIF":6.5,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74119107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Human-computer interaction (HCI) technology plays a critically essential role in the computer-aided design of railway line locations. However, the traditional interactive design with a mouse+keyboard cannot well meet the rapid generation requirements of the railway line during scheme discussion. This research presents a fitting algorithm for the rapid generation of railway lines by using a multi-touch gesture algorithm. The fitting method from free hand-drawing lines to satisfied railway lines is proposed. Then the interactive operation hand gestures are defined and implemented into the railway line location design. The hand-drawing lines generated by defined gestures are automatically fitted with the target horizontal line by using the inflection detection algorithm based on Euclidean Distance (ED). Meanwhile, the vertical line can be fitted by a similar algorithm with an extreme point-to-point (EPP) and chord-to-point distance accumulation (CPDA). Moreover, a real-world example verification is carried out. The multi-touch gesture algorithm is applied for the automatic fitting of the railway line. Compared with the traditional interactive methods, the consumption time of railway line generation by using the multi-touch interactive mode is decreased by about 15%. This research provides fundamental support for rapid scheme discussion of railway line generation based on natural HCI, which is well-matched with modern handheld devices, and the requirements of rapid selection as well as the quick comparison of railway line schemes in the early stage of design.
{"title":"A fitting algorithm based on multi-touch gesture for rapid generation of railway line","authors":"Liang Nie, Ruilin Zhang, Ting-dong Hu, Zhe Tang, Mingjing Fang, X. Lv, Ruitao Zhang","doi":"10.3233/ica-230697","DOIUrl":"https://doi.org/10.3233/ica-230697","url":null,"abstract":"Human-computer interaction (HCI) technology plays a critically essential role in the computer-aided design of railway line locations. However, the traditional interactive design with a mouse+keyboard cannot well meet the rapid generation requirements of the railway line during scheme discussion. This research presents a fitting algorithm for the rapid generation of railway lines by using a multi-touch gesture algorithm. The fitting method from free hand-drawing lines to satisfied railway lines is proposed. Then the interactive operation hand gestures are defined and implemented into the railway line location design. The hand-drawing lines generated by defined gestures are automatically fitted with the target horizontal line by using the inflection detection algorithm based on Euclidean Distance (ED). Meanwhile, the vertical line can be fitted by a similar algorithm with an extreme point-to-point (EPP) and chord-to-point distance accumulation (CPDA). Moreover, a real-world example verification is carried out. The multi-touch gesture algorithm is applied for the automatic fitting of the railway line. Compared with the traditional interactive methods, the consumption time of railway line generation by using the multi-touch interactive mode is decreased by about 15%. This research provides fundamental support for rapid scheme discussion of railway line generation based on natural HCI, which is well-matched with modern handheld devices, and the requirements of rapid selection as well as the quick comparison of railway line schemes in the early stage of design.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"96 1","pages":"135-150"},"PeriodicalIF":6.5,"publicationDate":"2023-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73227926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Muñoz-Montoro, Pablo Revuelta, Alberto Villalón-Fernández, Rubén Muñiz, J. Ranilla
. In this paper, a noninvasive portable prototype is presented for biomedical audio signal processing. The proposed prototype is suitable for monitoring the health of patients. The proposed hardware setup consists of a cost-effective microphone, multipurpose microcontroller and computing node that could be a mobile phone or general-purpose computer. Using parallel and high-performance techniques, this setup allows one to register and wirelessly multicast the recorded biomedical signals to computing nodes in real time. The developed prototype was used as a case study to estimate the heart rate (HR) from the captured biomedical audio signal. In this regard, the developed algorithm for estimating HR comprises three stages: preprocessing, separation, and HR estimation. In the first stage, the signal captured by the microphone is adapted for processing. Subsequently, a separation stage was proposed to alleviate the acoustic interference between the lungs and heart. The separation is performed by combining a non-negative matrix factorization algorithm, clustering approach, and soft-filter strategy. Finally, HR estimation was obtained using a novel and efficient method based on the autocorrelation function. The developed prototype could be used not only for the estimation of the HR, but also for the retrieval of other biomedical information related to the recording of cardiac or respiratory audio signals. The proposed method was evaluated using well-known datasets and compared with state-of-the-art algorithms for source-separation. The results showed that it is possible to obtain an accurate separation and reliable real-time estimation in terms of source separation metrics and relative error in the tested scenarios by combining multi-core architectures with parallel and high-performance techniques. Finally, the proposed prototype was validated in a real-world scenario.
{"title":"A system for biomedical audio signal processing based on high performance computing techniques","authors":"A. Muñoz-Montoro, Pablo Revuelta, Alberto Villalón-Fernández, Rubén Muñiz, J. Ranilla","doi":"10.3233/ICA-220686","DOIUrl":"https://doi.org/10.3233/ICA-220686","url":null,"abstract":". In this paper, a noninvasive portable prototype is presented for biomedical audio signal processing. The proposed prototype is suitable for monitoring the health of patients. The proposed hardware setup consists of a cost-effective microphone, multipurpose microcontroller and computing node that could be a mobile phone or general-purpose computer. Using parallel and high-performance techniques, this setup allows one to register and wirelessly multicast the recorded biomedical signals to computing nodes in real time. The developed prototype was used as a case study to estimate the heart rate (HR) from the captured biomedical audio signal. In this regard, the developed algorithm for estimating HR comprises three stages: preprocessing, separation, and HR estimation. In the first stage, the signal captured by the microphone is adapted for processing. Subsequently, a separation stage was proposed to alleviate the acoustic interference between the lungs and heart. The separation is performed by combining a non-negative matrix factorization algorithm, clustering approach, and soft-filter strategy. Finally, HR estimation was obtained using a novel and efficient method based on the autocorrelation function. The developed prototype could be used not only for the estimation of the HR, but also for the retrieval of other biomedical information related to the recording of cardiac or respiratory audio signals. The proposed method was evaluated using well-known datasets and compared with state-of-the-art algorithms for source-separation. The results showed that it is possible to obtain an accurate separation and reliable real-time estimation in terms of source separation metrics and relative error in the tested scenarios by combining multi-core architectures with parallel and high-performance techniques. Finally, the proposed prototype was validated in a real-world scenario.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"133 1","pages":"1-18"},"PeriodicalIF":6.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84772257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Enol García González, J. Villar, Qing Tan, J. Sedano, Camelia Chira
Multi-robot path planning has evolved from research to real applications in warehouses and other domains; the knowledge on this topic is reflected in the large amount of related research published in recent years on international journals. The main focus of existing research relates to the generation of efficient routes, relying the collision detection to the local sensory system and creating a solution based on local search methods. This approach implies the robots having a good sensory system and also the computation capabilities to take decisions on the fly. In some controlled environments, such as virtual labs or industrial plants, these restrictions overtake the actual needs as simpler robots are sufficient. Therefore, the multi-robot path planning must solve the collisions beforehand. This study focuses on the generation of efficient collision-free multi-robot path planning solutions for such controlled environments, extending our previous research. The proposal combines the optimization capabilities of the A* algorithm with the search capabilities of co-evolutionary algorithms. The outcome is a set of routes, either from A* or from the co-evolutionary process, that are collision-free; this set is generated in real-time and makes its implementation on edge-computing devices feasible. Although further research is needed to reduce the computational time, the computational experiments performed in this study confirm a good performance of the proposed approach in solving complex cases where well-known alternatives, such as M* or WHCA, fail in finding suitable solutions.
{"title":"An efficient multi-robot path planning solution using A* and coevolutionary algorithms","authors":"Enol García González, J. Villar, Qing Tan, J. Sedano, Camelia Chira","doi":"10.3233/ica-220695","DOIUrl":"https://doi.org/10.3233/ica-220695","url":null,"abstract":"Multi-robot path planning has evolved from research to real applications in warehouses and other domains; the knowledge on this topic is reflected in the large amount of related research published in recent years on international journals. The main focus of existing research relates to the generation of efficient routes, relying the collision detection to the local sensory system and creating a solution based on local search methods. This approach implies the robots having a good sensory system and also the computation capabilities to take decisions on the fly. In some controlled environments, such as virtual labs or industrial plants, these restrictions overtake the actual needs as simpler robots are sufficient. Therefore, the multi-robot path planning must solve the collisions beforehand. This study focuses on the generation of efficient collision-free multi-robot path planning solutions for such controlled environments, extending our previous research. The proposal combines the optimization capabilities of the A* algorithm with the search capabilities of co-evolutionary algorithms. The outcome is a set of routes, either from A* or from the co-evolutionary process, that are collision-free; this set is generated in real-time and makes its implementation on edge-computing devices feasible. Although further research is needed to reduce the computational time, the computational experiments performed in this study confirm a good performance of the proposed approach in solving complex cases where well-known alternatives, such as M* or WHCA, fail in finding suitable solutions.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"44 1","pages":"41-52"},"PeriodicalIF":6.5,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89819932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Various system identification (SI) techniques have been developed to ensure the sufficient structural performance of buildings. Recently, attempts have been made to solve the problem of the excessive computational time required for operational modal analysis (OMA), which is involved in SI, by using the deep learning (DL) algorithm and to overcome the limited applicability to structural problems of extended Kalman filter (EKF)-based SI technology through the development of a method enabling SI under unknown input conditions by adding a term for the input load to the algorithm. Although DL-based OMA methods and EKF-based SI techniques under unknown input conditions are being developed in various forms, they still produce incomplete identification processes when extracting the identification parameters. The neural network of the developed DL-based OMA method fails to extract all modal parameters perfectly, and EKF-based SI techniques has the limitations of a heavy algorithm and an increased computational burden with an input load term added to the algorithm. Therefore, this study proposes an EKF-based long short-term memory (EKF-LSTM) method that can identify modal parameters. The proposed EKF-LSTM method applies modal-expanded dynamic governing equations to the EKF to identify the modal parameters, where the input load used in the EKF algorithm is estimated using the LSTM method. The EKF-LSTM method can identify all modal parameters using the EKF, which is highly applicable to structural problems. Because the proposed method estimates the input load through an already trained LSTM network, there is no problem with computational burden when estimating the input load. The proposed EKF-LSTM method was verified using a numerical model with three degrees of freedom, and its effectiveness was confirmed by utilizing a steel frame structure model with three floors.
{"title":"Modal identification of building structures under unknown input conditions using extended Kalman filter and long-short term memory","authors":"Da Yo Yun, H. Park","doi":"10.3233/ica-220696","DOIUrl":"https://doi.org/10.3233/ica-220696","url":null,"abstract":"Various system identification (SI) techniques have been developed to ensure the sufficient structural performance of buildings. Recently, attempts have been made to solve the problem of the excessive computational time required for operational modal analysis (OMA), which is involved in SI, by using the deep learning (DL) algorithm and to overcome the limited applicability to structural problems of extended Kalman filter (EKF)-based SI technology through the development of a method enabling SI under unknown input conditions by adding a term for the input load to the algorithm. Although DL-based OMA methods and EKF-based SI techniques under unknown input conditions are being developed in various forms, they still produce incomplete identification processes when extracting the identification parameters. The neural network of the developed DL-based OMA method fails to extract all modal parameters perfectly, and EKF-based SI techniques has the limitations of a heavy algorithm and an increased computational burden with an input load term added to the algorithm. Therefore, this study proposes an EKF-based long short-term memory (EKF-LSTM) method that can identify modal parameters. The proposed EKF-LSTM method applies modal-expanded dynamic governing equations to the EKF to identify the modal parameters, where the input load used in the EKF algorithm is estimated using the LSTM method. The EKF-LSTM method can identify all modal parameters using the EKF, which is highly applicable to structural problems. Because the proposed method estimates the input load through an already trained LSTM network, there is no problem with computational burden when estimating the input load. The proposed EKF-LSTM method was verified using a numerical model with three degrees of freedom, and its effectiveness was confirmed by utilizing a steel frame structure model with three floors.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"85 1","pages":"185-201"},"PeriodicalIF":6.5,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80479774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Grosset, A. Ndao, A. Fougères, M. Djoko-Kouam, C. Couturier, J. Bonnin
Industry 4.0 leads to a strong digitalization of industrial processes, but also a significant increase in communication and cooperation between the machines that make it up. This is the case with autonomous industrial vehicles (AIVs) and other cooperative mobile robots which are multiplying in factories, often in the form of fleets of vehicles, and whose intelligence and autonomy are increasing. While the autonomy of autonomous vehicles has been well characterized in the field of road and road transport, this is not the case for the autonomous vehicles used in industry. The establishment and deployment of AIV fleets raises several challenges, all of which depend on the actual level of autonomy of the AIVs: acceptance by employees, vehicle location, traffic fluidity, collision detection, or vehicle perception of changing environments. Thus, simulation serves to account for the constraints and requirements formulated by the manufacturers and future users of AIVs. In this paper, after having proposed a broad state of the art on the problems to be solved in order to simulate AIVs before proceeding to experiments in real conditions, we present a method to estimate positions of AIVs moving in a closed industrial environment, the extension of a collision detection algorithm to deal with the obstacle avoidance issue, and the development of an agent-based simulation platform for simulating these two methods and algorithms. The resulting/final/subsequent simulation will allow us to experiment in real conditions.
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