Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00015
Yapeng Huang, Jun Shen
Focusing on the lack of implicit knowledge teaching in online teaching activities and combining related research achievements of learning theory and knowledge model, this paper proposes an algorithm for learning path recommendation which is based on ant colony algorithm. Comprehensively considering the students' cognitive style, knowledge basis and group preference, this algorithm takes implicit knowledge as the essential learning goal and recommends personalized learning paths to them. The experimental results prove that the algorithm can effectively improve students' academic performance and learning efficiency.
{"title":"An Implicit Knowledge Oriented Algorithm for Learning Path Recommendation","authors":"Yapeng Huang, Jun Shen","doi":"10.1109/ICCIA.2018.00015","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00015","url":null,"abstract":"Focusing on the lack of implicit knowledge teaching in online teaching activities and combining related research achievements of learning theory and knowledge model, this paper proposes an algorithm for learning path recommendation which is based on ant colony algorithm. Comprehensively considering the students' cognitive style, knowledge basis and group preference, this algorithm takes implicit knowledge as the essential learning goal and recommends personalized learning paths to them. The experimental results prove that the algorithm can effectively improve students' academic performance and learning efficiency.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115192497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/iccia.2018.00005
{"title":"ICCIA 2018 Preface","authors":"","doi":"10.1109/iccia.2018.00005","DOIUrl":"https://doi.org/10.1109/iccia.2018.00005","url":null,"abstract":"","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130011052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00039
Xiaojuan Wang, Ying Zeng, Jun Shu, Chi Zhang, Bin Yan
Eye movements obtained during eye tracking include both the fixation location and cognitive activities of the subject when viewing the remote sensing images. Aiming at the problem that the existing region of interest analysis methods based on the eye movement do not determine whether the area contains targets or not, in this paper a method was presented to predict the targets in the regions of interest using cognitive activities from eye movement. The method realized the detection and location of targets in remote-sensing images through the combination of fixation location and cognitive activity in eye movements. Experiments showed that the cognitive activities related to fixations make significant contribution to target prediction in the remote sensing image with complex backgrounds.
{"title":"Eye Fixation Related Cognitive Activities for Detecting Targets in Remote Sensing Images","authors":"Xiaojuan Wang, Ying Zeng, Jun Shu, Chi Zhang, Bin Yan","doi":"10.1109/ICCIA.2018.00039","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00039","url":null,"abstract":"Eye movements obtained during eye tracking include both the fixation location and cognitive activities of the subject when viewing the remote sensing images. Aiming at the problem that the existing region of interest analysis methods based on the eye movement do not determine whether the area contains targets or not, in this paper a method was presented to predict the targets in the regions of interest using cognitive activities from eye movement. The method realized the detection and location of targets in remote-sensing images through the combination of fixation location and cognitive activity in eye movements. Experiments showed that the cognitive activities related to fixations make significant contribution to target prediction in the remote sensing image with complex backgrounds.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117083199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/iccia.2018.00021
Ben-Da Zhou, Zhao Pan, Zhang Jinbo
Based on the analysis of local monotonic of modularity function, this paper designs a fast and effective mutation operator, and then proposes an improved Estimation of Distribution Algorithm (EDA) for solving community detection problem. The proposed algorithm is tested on basic network and big scale complex network. Experimental results show that this algorithm can get 0.419 8 for the average Q function while running 100 times, has better performance than Girvan-Newman(GN) algorithm, Fast Newman (FN) algorithm and Tasgin Genetic Algorithm (TGA).
{"title":"The Improved Estimation of Distribution Algorithms for Community Detection","authors":"Ben-Da Zhou, Zhao Pan, Zhang Jinbo","doi":"10.1109/iccia.2018.00021","DOIUrl":"https://doi.org/10.1109/iccia.2018.00021","url":null,"abstract":"Based on the analysis of local monotonic of modularity function, this paper designs a fast and effective mutation operator, and then proposes an improved Estimation of Distribution Algorithm (EDA) for solving community detection problem. The proposed algorithm is tested on basic network and big scale complex network. Experimental results show that this algorithm can get 0.419 8 for the average Q function while running 100 times, has better performance than Girvan-Newman(GN) algorithm, Fast Newman (FN) algorithm and Tasgin Genetic Algorithm (TGA).","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121453694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/iccia.2018.00002
{"title":"Title Page iii","authors":"","doi":"10.1109/iccia.2018.00002","DOIUrl":"https://doi.org/10.1109/iccia.2018.00002","url":null,"abstract":"","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124156705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/iccia.2018.00018
Xiangguang Dai, Yingji Cui, Zheng Chen, Yi Yang
As Internet expanding into offline, the traditional retail industry began to use the personalized recommendation algorithm to increase user stickiness, conversion and business income. Without considering the data segmentation problem, traditional recommendation algorithm did not perform well in the traditional business data. Accordingly, we considered the interest spread characteristic of retail industry behavior, adopted the method of complex network to construct a personalized recommendation algorithm using the segmentation data set. By using a real sales dataset of a large supermarket, we provided an evaluation of our algorithm. The results show that our algorithm have much better performance in accuracy and recall than the traditional ones, but with the disadvantage of being less coverage.
{"title":"A Network-Based Recommendation Algorithm","authors":"Xiangguang Dai, Yingji Cui, Zheng Chen, Yi Yang","doi":"10.1109/iccia.2018.00018","DOIUrl":"https://doi.org/10.1109/iccia.2018.00018","url":null,"abstract":"As Internet expanding into offline, the traditional retail industry began to use the personalized recommendation algorithm to increase user stickiness, conversion and business income. Without considering the data segmentation problem, traditional recommendation algorithm did not perform well in the traditional business data. Accordingly, we considered the interest spread characteristic of retail industry behavior, adopted the method of complex network to construct a personalized recommendation algorithm using the segmentation data set. By using a real sales dataset of a large supermarket, we provided an evaluation of our algorithm. The results show that our algorithm have much better performance in accuracy and recall than the traditional ones, but with the disadvantage of being less coverage.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126445480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00031
Azadeh Sarkheyli, Arezoo Sarkheyli-Hägele, W. Song
A dynamic Risk Management (RM) provides monitoring, recognition, assessment, and follow-up action to reduce the risk whenever it rises. The main problem with dynamic RM (when applied to plan for, how the unknown risk in unexpected conditions should be addressed in information systems) is to design an especial control to recover/avoid of risks/attacks that is proposed in this research. The methodology, called Dynamic Intelligent RM (DIRM) is comprised of four phases which are interactively linked; (1) Aggregation of data and information (2) Risk identification (3) RM using an optional control and (4) RM using an especial control. This study, therefore, investigated the use of artificial neural networks to improve risk identification via adaptive neural fuzzy interface systems and control specification using learning vector quantization. Further experimental investigations are needed to estimate the results of DIRM toward unexpected conditions in the real environment.
{"title":"Development of Dynamic Intelligent Risk Management Approach","authors":"Azadeh Sarkheyli, Arezoo Sarkheyli-Hägele, W. Song","doi":"10.1109/ICCIA.2018.00031","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00031","url":null,"abstract":"A dynamic Risk Management (RM) provides monitoring, recognition, assessment, and follow-up action to reduce the risk whenever it rises. The main problem with dynamic RM (when applied to plan for, how the unknown risk in unexpected conditions should be addressed in information systems) is to design an especial control to recover/avoid of risks/attacks that is proposed in this research. The methodology, called Dynamic Intelligent RM (DIRM) is comprised of four phases which are interactively linked; (1) Aggregation of data and information (2) Risk identification (3) RM using an optional control and (4) RM using an especial control. This study, therefore, investigated the use of artificial neural networks to improve risk identification via adaptive neural fuzzy interface systems and control specification using learning vector quantization. Further experimental investigations are needed to estimate the results of DIRM toward unexpected conditions in the real environment.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122069878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00016
Feng-Cheng Yang, Ren-Fu Li
This paper presents a novel heuristic optimization algorithm for discrete optimization problems, the Bandwidth Restricted Transmission-Simulated Optimization Algorithm (BRT-S). This algorithm imitates the intellective behaviors of human in managing network transmission. BRT-S is a constructive heuristic algorithm whose optimization procedures simulate processes of data transferring and management operations over the network. A population of solution agents mimicking message transmitters on networks is deployed to quest for optimal solutions. The algorithm however restricts the resource utilized in solution search mimicking the bandwidth resource is limited in network transmission. As a result, agents must compete with others to obtain solution construction resources. Due to the mimicked bandwidth restriction, not every agent is able to complete a solution construction. Only constructed solutions are subject to objective value evaluations. In each evolution iteration, bandwidth resources are separately modulated by conducting bandwidth deterioration, enhancement, or depletion, on the basis of the solution qualities obtained. To illustrate the operation procedures of the algorithm, a BRT-S computation model for solving the Traveling Salesman Problem is presented and the solving system is implemented for benchmark testing. Numerical results of the tests indicate that given similar computation resources, the algorithm generates better solutions than other meta heuristic algorithms, such as ACO and GA.
{"title":"A Human Intelligence Inspired Meta Heuristic Optimization Algorithm for TSPs","authors":"Feng-Cheng Yang, Ren-Fu Li","doi":"10.1109/ICCIA.2018.00016","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00016","url":null,"abstract":"This paper presents a novel heuristic optimization algorithm for discrete optimization problems, the Bandwidth Restricted Transmission-Simulated Optimization Algorithm (BRT-S). This algorithm imitates the intellective behaviors of human in managing network transmission. BRT-S is a constructive heuristic algorithm whose optimization procedures simulate processes of data transferring and management operations over the network. A population of solution agents mimicking message transmitters on networks is deployed to quest for optimal solutions. The algorithm however restricts the resource utilized in solution search mimicking the bandwidth resource is limited in network transmission. As a result, agents must compete with others to obtain solution construction resources. Due to the mimicked bandwidth restriction, not every agent is able to complete a solution construction. Only constructed solutions are subject to objective value evaluations. In each evolution iteration, bandwidth resources are separately modulated by conducting bandwidth deterioration, enhancement, or depletion, on the basis of the solution qualities obtained. To illustrate the operation procedures of the algorithm, a BRT-S computation model for solving the Traveling Salesman Problem is presented and the solving system is implemented for benchmark testing. Numerical results of the tests indicate that given similar computation resources, the algorithm generates better solutions than other meta heuristic algorithms, such as ACO and GA.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129388668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00011
Vidya Diantorio Putri, K. Komarudin, A. R. Destyanto
Mass Rapid Transit (MRT) Jakarta is one of the new urban transportation in Greater Jakarta area which will be operated in early 2019. The development period has been started in 2010. A research has been conducted to determine its train specification, including train set and car number in 2010. Time revealed that the based data for that research, forecasted number of Jakarta population, is not fits the actual number. This research goal is to determine the train specification, which are the number of MRT Jakarta train set and number of car for each train set to reach its headway target by considering MRT Jakarta daily passenger target based on actual number of Jakarta population. The researcher uses ProModel 7.5 as the tool to simulate 12 optional policy. These 12 optional policies is made of combined three control variable, which are train set, car number, and headway. Researcher use the number of passenger compared to MRT Jakarta daily passenger target as the indicator to choose the best policy. Based on the result of this research, the best train specification policy that could reach the 5 minutes headway MRT Jakarta target is 7 train set and 6 cars for each set.
{"title":"The Determination of MRT (Mass Rapid Transit) Jakarta Train Specification to Reach Headway Target by Using ProModel","authors":"Vidya Diantorio Putri, K. Komarudin, A. R. Destyanto","doi":"10.1109/ICCIA.2018.00011","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00011","url":null,"abstract":"Mass Rapid Transit (MRT) Jakarta is one of the new urban transportation in Greater Jakarta area which will be operated in early 2019. The development period has been started in 2010. A research has been conducted to determine its train specification, including train set and car number in 2010. Time revealed that the based data for that research, forecasted number of Jakarta population, is not fits the actual number. This research goal is to determine the train specification, which are the number of MRT Jakarta train set and number of car for each train set to reach its headway target by considering MRT Jakarta daily passenger target based on actual number of Jakarta population. The researcher uses ProModel 7.5 as the tool to simulate 12 optional policy. These 12 optional policies is made of combined three control variable, which are train set, car number, and headway. Researcher use the number of passenger compared to MRT Jakarta daily passenger target as the indicator to choose the best policy. Based on the result of this research, the best train specification policy that could reach the 5 minutes headway MRT Jakarta target is 7 train set and 6 cars for each set.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127032989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00030
Crino Shin, J. Yun, Seunghyun Jeong, Yongsik Jin
This paper presents a Remaining Useful Life (RUL) prediction method for a speed reducer based on denoising au- to-encoder (DAE). Constructing the efficiency map of the re- ducer is an important process for predicting the life span. However, due to the situational constraints that occur, un- measured intervals hinder the completion of the efficiency map. to solve this problem, we propose a method that can pre- dict and reconstruct an unmeasured interval effectively and reliably by using DAE. In addition, we examine the applicabil- ity of the proposed algorithm through experiments that assume various situations.
{"title":"Predicting Unmeasured Region of the Efficiency Map of a Speed Reducer Using a Denoising Auto-Encoder","authors":"Crino Shin, J. Yun, Seunghyun Jeong, Yongsik Jin","doi":"10.1109/ICCIA.2018.00030","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00030","url":null,"abstract":"This paper presents a Remaining Useful Life (RUL) prediction method for a speed reducer based on denoising au- to-encoder (DAE). Constructing the efficiency map of the re- ducer is an important process for predicting the life span. However, due to the situational constraints that occur, un- measured intervals hinder the completion of the efficiency map. to solve this problem, we propose a method that can pre- dict and reconstruct an unmeasured interval effectively and reliably by using DAE. In addition, we examine the applicabil- ity of the proposed algorithm through experiments that assume various situations.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126019877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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