Pub Date : 2019-02-01DOI: 10.1109/KBEI.2019.8734903
M. Navabi, N. Davoodi
In this paper focused on design of a second order sliding mode controller for a fixed wing airplane using real twisting algorithm. Simple sliding mode controller creates chattering in the system. Therefore, to avoid this problem, higher order sliding mode controllers as a robust controller is preferred. The design of this controller has two steps. At first, a suitable sliding manifold will be selected. Then, the controller is designed using real twisting algorithm which is a method for second order sliding mode controller design. In this algorithm the states of the system twist around the sliding surface and remain on it. Moreover, to compare the performance of the controller, a first order sliding mode controller is designed. Results demonstrate that, with real twisting method, states of the system converge to trim point in a finite time and system has good performance under this controller.
{"title":"Design of a Robust Controller Using Real Twisting Algorithm for a Fixed Wing Airplane","authors":"M. Navabi, N. Davoodi","doi":"10.1109/KBEI.2019.8734903","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734903","url":null,"abstract":"In this paper focused on design of a second order sliding mode controller for a fixed wing airplane using real twisting algorithm. Simple sliding mode controller creates chattering in the system. Therefore, to avoid this problem, higher order sliding mode controllers as a robust controller is preferred. The design of this controller has two steps. At first, a suitable sliding manifold will be selected. Then, the controller is designed using real twisting algorithm which is a method for second order sliding mode controller design. In this algorithm the states of the system twist around the sliding surface and remain on it. Moreover, to compare the performance of the controller, a first order sliding mode controller is designed. Results demonstrate that, with real twisting method, states of the system converge to trim point in a finite time and system has good performance under this controller.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125333414","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8735001
Sara Nazififard, S. Jafari, H. Z. Matin, H. Yazdani
In learning contexts, gamification is a technique to motivate learners and enhance their participation in learning activities by applying game elements and components. But it still pays little attention to using gamification in Adult learning activities. Through a systematic literature review, this study investigates the literature on the motivational and behavioral theories underlying gamification in the context of learning to synthesize the essential factors to improve learning outcomes. This paper presents a conceptual model of gamification in a learning context. A theory-driven model was created in order to categorize into a multi-dimensional model. In addition, this model can be extended to any kind of games not only educational games because the whole gaming experience is based on the same theory as human learning. It originates from behavioral science and it has progressed well-stablished learning algorithm. By investigating and synthesizing the earlier studies and categorizing them in accordance with a contemporary approach, a conceptual model for gamification of adult learning has been proposed. Then in order to validate and test this theory-driven model should be implemented and tested in experimental studies involving organization employees.
{"title":"A Model for Utilizing the Potential of Gamification in Learning","authors":"Sara Nazififard, S. Jafari, H. Z. Matin, H. Yazdani","doi":"10.1109/KBEI.2019.8735001","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735001","url":null,"abstract":"In learning contexts, gamification is a technique to motivate learners and enhance their participation in learning activities by applying game elements and components. But it still pays little attention to using gamification in Adult learning activities. Through a systematic literature review, this study investigates the literature on the motivational and behavioral theories underlying gamification in the context of learning to synthesize the essential factors to improve learning outcomes. This paper presents a conceptual model of gamification in a learning context. A theory-driven model was created in order to categorize into a multi-dimensional model. In addition, this model can be extended to any kind of games not only educational games because the whole gaming experience is based on the same theory as human learning. It originates from behavioral science and it has progressed well-stablished learning algorithm. By investigating and synthesizing the earlier studies and categorizing them in accordance with a contemporary approach, a conceptual model for gamification of adult learning has been proposed. Then in order to validate and test this theory-driven model should be implemented and tested in experimental studies involving organization employees.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126050762","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8735026
Razieh Moradi, H. Nezamabadi-pour, Mohadeseh Soleimanpour
In this paper, we propose a modified distributed bee algorithm (MDBA) for task allocation in a swarm of robots. In MDBA, a tournament selection mechanism is proposed to improve the selection ability of the algorithm. In the proposed scenario, task allocation is to assign the robots to the found targets in a 2-D arena. The expected distribution is obtained from the targets’ qualities that are represented as scalar values. We tested the scalability of the proposed MDBA algorithm in terms of number of robots and number of targets. The simulation results show that by increasing the robot swarm’s size, the distribution error is decreased. The results obtained confirm the ability of the proposed MDBA.
{"title":"Modified Distributed Bee Algorithm in Task Allocation of Swarm Robotic","authors":"Razieh Moradi, H. Nezamabadi-pour, Mohadeseh Soleimanpour","doi":"10.1109/KBEI.2019.8735026","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735026","url":null,"abstract":"In this paper, we propose a modified distributed bee algorithm (MDBA) for task allocation in a swarm of robots. In MDBA, a tournament selection mechanism is proposed to improve the selection ability of the algorithm. In the proposed scenario, task allocation is to assign the robots to the found targets in a 2-D arena. The expected distribution is obtained from the targets’ qualities that are represented as scalar values. We tested the scalability of the proposed MDBA algorithm in terms of number of robots and number of targets. The simulation results show that by increasing the robot swarm’s size, the distribution error is decreased. The results obtained confirm the ability of the proposed MDBA.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121835816","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8735036
Arman Yanpi, M. Taheri
Multi label classification is a challenging task in machine learning concerned with assigning a sample to a subset of available label set. Meaning, a sample can belong to multiple labels. Furthermore, high dimensionality of data and complex correlation between labels makes it even more interesting. For this reason, it attracted many researchers in recent years. classifier-chains (CC), one of well-known methods for multi label classification which is based on binary relevance (BR) method, incorporates label correlation by assuming an order for labels and inserting previous label outputs in feature space and achieves higher performance while still retaining relatively low time complexity. But using predicted labels as features might not be very interpretable with regards to integrating label correlation into the model, especially considering there could be different types of features in a dataset. In this paper, we propose an approach for using correlation among labels based on structure of CC by defining a large-margin model between two predicted labels. Thus directly exploiting the correlation between them in a more interpretable way. The proposed approach is evaluated using 9 multi label datasets and 2 evaluation metrics. Empirical experiments show promising results and demonstrate the effectiveness of proposed method against classifier chains algorithm.
{"title":"A Large-Margin Approach for Multi-Label Classification Based on Correlation Between Labels","authors":"Arman Yanpi, M. Taheri","doi":"10.1109/KBEI.2019.8735036","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735036","url":null,"abstract":"Multi label classification is a challenging task in machine learning concerned with assigning a sample to a subset of available label set. Meaning, a sample can belong to multiple labels. Furthermore, high dimensionality of data and complex correlation between labels makes it even more interesting. For this reason, it attracted many researchers in recent years. classifier-chains (CC), one of well-known methods for multi label classification which is based on binary relevance (BR) method, incorporates label correlation by assuming an order for labels and inserting previous label outputs in feature space and achieves higher performance while still retaining relatively low time complexity. But using predicted labels as features might not be very interpretable with regards to integrating label correlation into the model, especially considering there could be different types of features in a dataset. In this paper, we propose an approach for using correlation among labels based on structure of CC by defining a large-margin model between two predicted labels. Thus directly exploiting the correlation between them in a more interpretable way. The proposed approach is evaluated using 9 multi label datasets and 2 evaluation metrics. Empirical experiments show promising results and demonstrate the effectiveness of proposed method against classifier chains algorithm.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"59 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133218324","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8734918
R. Besharati, Mohammad Hossein Rezvani
One of the significant issues in fog computing environments is computation offloading. In order to do this process, the communications between the fog and cloud nodes should be investigated. In the literature, a great body of research exists in which the researchers proposed numerous optimization methods regard the subject of offloading in fog networks. These proposals have been implemented taking into account service level agreements (SLAs). In this paper, we propose an optimization method for modeling the interactions of offloading process using rich theory of microeconomics. We model the offloading interactions based on auction mechanism. Then, we modelled and formulated the communications between fog nodes and the cloud entity. Our model takes into account the specifications and limitations of the underlying physical infrastructure such as paths and capacity of each path. These paths are used during computation offloading operations. In our proposed auction economy, the bandwidth of physical links plays the role of the commodity. Finally, the auction is run between the cloud and fog nodes as provider and consumer respectively.
{"title":"A Prototype Auction-based Mechanism for Computation Offloading in Fog-cloud Environments","authors":"R. Besharati, Mohammad Hossein Rezvani","doi":"10.1109/KBEI.2019.8734918","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734918","url":null,"abstract":"One of the significant issues in fog computing environments is computation offloading. In order to do this process, the communications between the fog and cloud nodes should be investigated. In the literature, a great body of research exists in which the researchers proposed numerous optimization methods regard the subject of offloading in fog networks. These proposals have been implemented taking into account service level agreements (SLAs). In this paper, we propose an optimization method for modeling the interactions of offloading process using rich theory of microeconomics. We model the offloading interactions based on auction mechanism. Then, we modelled and formulated the communications between fog nodes and the cloud entity. Our model takes into account the specifications and limitations of the underlying physical infrastructure such as paths and capacity of each path. These paths are used during computation offloading operations. In our proposed auction economy, the bandwidth of physical links plays the role of the commodity. Finally, the auction is run between the cloud and fog nodes as provider and consumer respectively.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133682538","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8735040
B. Mohammadi, J. Nourinia, C. Ghobadi, F. Alizadeh, Seyed Vahid Masuminia
A novel broadband reflectarray (RA) antenna for 3U CubeSat applications is investigated. A novel frequency selective surface (FSS) in the RA as ground plane for reducing radar cross section (RCS) and signals interference with other communication systems working in other frequency bands is applied. The RA divided to three panels and folded on the sides of the CubeSat to reduce the stowed volume. A novel circular polarization (CP) feed antenna with two stacked patches on two thick substrates with lossy dielectric constant is used to extend the 3dB axial ratio.
{"title":"Novel Broadband 3U CubeSat Reflectarray Antenna","authors":"B. Mohammadi, J. Nourinia, C. Ghobadi, F. Alizadeh, Seyed Vahid Masuminia","doi":"10.1109/KBEI.2019.8735040","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735040","url":null,"abstract":"A novel broadband reflectarray (RA) antenna for 3U CubeSat applications is investigated. A novel frequency selective surface (FSS) in the RA as ground plane for reducing radar cross section (RCS) and signals interference with other communication systems working in other frequency bands is applied. The RA divided to three panels and folded on the sides of the CubeSat to reduce the stowed volume. A novel circular polarization (CP) feed antenna with two stacked patches on two thick substrates with lossy dielectric constant is used to extend the 3dB axial ratio.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114572753","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8735068
Mahdi Salehi, F. Farivar
Car wing has many capabilities to work on and benefit from. There are different types of wings and spoilers in sport cars that are being used to help having better acceleration, braking, etc. Generally after aerodynamic analysis of wings or rear spoilers, and simulation the second step is to find the best control system to achieve maximum advantages from wings and spoilers. In other words, the wing working time is during car’s cornering and turning on different angels, braking or accelerating that is the time for a control system to operate. In this paper the goal is to implement state feedback tracking control system and optimization of the system by LQR method around equilibrium and operating points of the system specially during cornering of the vehicle. So to obtain the goal, the first step is to review previous works and benefit from. Then the second section is considered for mathematical calculation and the system dynamics plus design of mechanical components and assembled system by CATIA software. After that the control model is extracted for the control system. Furthermore the control system, which is tracking control system, is designed, implemented and the results are shown by figures and plots. The final step is to optimize the control system by LQR optimal control method and the results are compared to other methods. In this article the control system is simulated by MATLAB software.
{"title":"State Feedback Control Design of Cars Wings in Order to Improve Road-Holding on Corners of Roads","authors":"Mahdi Salehi, F. Farivar","doi":"10.1109/KBEI.2019.8735068","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735068","url":null,"abstract":"Car wing has many capabilities to work on and benefit from. There are different types of wings and spoilers in sport cars that are being used to help having better acceleration, braking, etc. Generally after aerodynamic analysis of wings or rear spoilers, and simulation the second step is to find the best control system to achieve maximum advantages from wings and spoilers. In other words, the wing working time is during car’s cornering and turning on different angels, braking or accelerating that is the time for a control system to operate. In this paper the goal is to implement state feedback tracking control system and optimization of the system by LQR method around equilibrium and operating points of the system specially during cornering of the vehicle. So to obtain the goal, the first step is to review previous works and benefit from. Then the second section is considered for mathematical calculation and the system dynamics plus design of mechanical components and assembled system by CATIA software. After that the control model is extracted for the control system. Furthermore the control system, which is tracking control system, is designed, implemented and the results are shown by figures and plots. The final step is to optimize the control system by LQR optimal control method and the results are compared to other methods. In this article the control system is simulated by MATLAB software.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"296 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123460742","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8734974
Niyoosha Dallalazar, A. Ayatollahi, M. Habibi, A. Kermani
Intravascular optical coherence tomography IVOCT is a catheter-based imaging modality that uses near-infrared light, to produce high-resolution cross-sectional images of the vessel wall. Segmentation of the vessel wall is important to indicate stenosis and analyze atherosclerotic plaques. In this study we use the recently proposed region detector, named Extremal Region of Extremum Level (EREL), to detect the lumen and media contours in IVOCT frames, and then we used a region selection method to detect the most precise lumen and media contours from the extracted ERELs. We evaluated the proposed method on the dataset containing 142 IVOCT images. We get, the average Hausdorff Distances (HD) and Dice metric (DSC) between the extracted ERELs and the lumen and media contours, 0.045 mm, 0.141 mm and 0.986, 0.96, respectively. The results of our study showed that the IVOCT image segmentation using the proposed method is more robust and more precise than state-of-the-art.
血管内光学相干断层扫描(IVOCT)是一种基于导管的成像方式，使用近红外光产生血管壁的高分辨率横截面图像。血管壁的分割对于显示狭窄和分析动脉粥样硬化斑块很重要。在本研究中，我们使用最近提出的区域检测器——极值水平的极值区域(extreme region of Extremum Level, EREL)来检测IVOCT帧中的腔体和介质轮廓，然后我们使用区域选择方法从提取的EREL中检测出最精确的腔体和介质轮廓。我们在包含142张IVOCT图像的数据集上评估了所提出的方法。我们得到的平均Hausdorff距离(HD)和Dice度量(DSC)在提取的ERELs与腔体和介质轮廓之间分别为0.045 mm, 0.141 mm和0.986,0.96。研究结果表明，使用该方法进行的IVOCT图像分割比现有方法具有更强的鲁棒性和精度。
{"title":"Automatic vessel wall segmentation of IVOCT images using region detection EREL algorithm","authors":"Niyoosha Dallalazar, A. Ayatollahi, M. Habibi, A. Kermani","doi":"10.1109/KBEI.2019.8734974","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734974","url":null,"abstract":"Intravascular optical coherence tomography IVOCT is a catheter-based imaging modality that uses near-infrared light, to produce high-resolution cross-sectional images of the vessel wall. Segmentation of the vessel wall is important to indicate stenosis and analyze atherosclerotic plaques. In this study we use the recently proposed region detector, named Extremal Region of Extremum Level (EREL), to detect the lumen and media contours in IVOCT frames, and then we used a region selection method to detect the most precise lumen and media contours from the extracted ERELs. We evaluated the proposed method on the dataset containing 142 IVOCT images. We get, the average Hausdorff Distances (HD) and Dice metric (DSC) between the extracted ERELs and the lumen and media contours, 0.045 mm, 0.141 mm and 0.986, 0.96, respectively. The results of our study showed that the IVOCT image segmentation using the proposed method is more robust and more precise than state-of-the-art.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123117326","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8734995
Masoud Shirzadeh, M. Shojaeefard, A. Amirkhani, H. Behroozi
In this paper, a nonlinear controller, which can be updated online by means of fuzzy logic, has been proposed for tracking the trajectory of a car-like robot. The advantage of this control scheme is that it eliminates the effects of model disturbances and uncertainties, which cannot be avoided; and especially when we consider the difficult task of determining the exact kinematic and dynamic models of car-like robots. The proposed approach comprises a robust nonlinear section that uses the sliding mode control and a fuzzy section that can update, online, parameters of the nonlinear controller. The stability and the error convergence of the closed-loop system are verified through the Lyapunov criterion. A fuzzy system is designed to deal with the chattering of the car-like robot. In addition to the gains of the sign function, there are also constant parameters in our controller, which are determined by using a genetic algorithm. To show the effectiveness of the proposed design, simulations are performed by considering un-ideal effects such as uncertainties and external disturbances.
{"title":"Adaptive fuzzy nonlinear sliding-mode controller for a car-like robot","authors":"Masoud Shirzadeh, M. Shojaeefard, A. Amirkhani, H. Behroozi","doi":"10.1109/KBEI.2019.8734995","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734995","url":null,"abstract":"In this paper, a nonlinear controller, which can be updated online by means of fuzzy logic, has been proposed for tracking the trajectory of a car-like robot. The advantage of this control scheme is that it eliminates the effects of model disturbances and uncertainties, which cannot be avoided; and especially when we consider the difficult task of determining the exact kinematic and dynamic models of car-like robots. The proposed approach comprises a robust nonlinear section that uses the sliding mode control and a fuzzy section that can update, online, parameters of the nonlinear controller. The stability and the error convergence of the closed-loop system are verified through the Lyapunov criterion. A fuzzy system is designed to deal with the chattering of the car-like robot. In addition to the gains of the sign function, there are also constant parameters in our controller, which are determined by using a genetic algorithm. To show the effectiveness of the proposed design, simulations are performed by considering un-ideal effects such as uncertainties and external disturbances.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123950620","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8735063
M. Golchin
Forecasting the demand of customers has a main role for managing the cost of marketing. Therefore, using a tool for forecasting the demand is vital for companies. There are many tools for forecasting and predicting the demand as time series. In this study a new hybrid model which contains fuzzy inference system and cellular automata has been developed. The results showed that, considering the information of more neighbor customers may cause more reliable forecasting and more complicated, fuzzy system may cause better performance for predicting the demand.
{"title":"Companies Products Demands Forecasting using Learning Fuzzy Cellular Automata Model. Case Study: Barij Essence Pharmaceutical Company","authors":"M. Golchin","doi":"10.1109/KBEI.2019.8735063","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735063","url":null,"abstract":"Forecasting the demand of customers has a main role for managing the cost of marketing. Therefore, using a tool for forecasting the demand is vital for companies. There are many tools for forecasting and predicting the demand as time series. In this study a new hybrid model which contains fuzzy inference system and cellular automata has been developed. The results showed that, considering the information of more neighbor customers may cause more reliable forecasting and more complicated, fuzzy system may cause better performance for predicting the demand.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124268549","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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