Pub Date : 2021-09-12DOI: 10.1109/msmc.2022.3148569
A. Zare, A. Shoeibi, Narges Shafaei Bajestani, Parisa Moridian, R. Alizadehsani, Majid Halaji, A. Khosravi
Many studies have been performed to handle the uncertainties in the data using type-1 fuzzy regression (FR). Few type-2 fuzzy (T2F) regression studies have used interval type-2 (IT2) for indeterminate modeling using type-1 fuzzy membership. The current article proposes a triangular T2F regression (TT2FR) model to ameliorate the efficiency of the model by handling the uncertainty in the data. The triangular secondary membership function is used instead of widely used interval-type models. In the proposed model, vagueness in primary and secondary fuzzy sets is minimized, and also, a specified x-plane of the observed value is included in the same ${alpha}$-plane of the predicted value. Complex calculations of the T2F model are simplified by reducing the 3D T2F set into 2D IT2 fuzzy models.
{"title":"Accurate Prediction Using Triangular Type-2 Fuzzy Linear Regression: Simplifying Complex T2F Calculations","authors":"A. Zare, A. Shoeibi, Narges Shafaei Bajestani, Parisa Moridian, R. Alizadehsani, Majid Halaji, A. Khosravi","doi":"10.1109/msmc.2022.3148569","DOIUrl":"https://doi.org/10.1109/msmc.2022.3148569","url":null,"abstract":"Many studies have been performed to handle the uncertainties in the data using type-1 fuzzy regression (FR). Few type-2 fuzzy (T2F) regression studies have used interval type-2 (IT2) for indeterminate modeling using type-1 fuzzy membership. The current article proposes a triangular T2F regression (TT2FR) model to ameliorate the efficiency of the model by handling the uncertainty in the data. The triangular secondary membership function is used instead of widely used interval-type models. In the proposed model, vagueness in primary and secondary fuzzy sets is minimized, and also, a specified x-plane of the observed value is included in the same ${alpha}$-plane of the predicted value. Complex calculations of the T2F model are simplified by reducing the 3D T2F set into 2D IT2 fuzzy models.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"86 1","pages":"51-60"},"PeriodicalIF":3.2,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83757229","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 : 2021-07-15DOI: 10.1109/MSMC.2021.3077725
S. Nahavandi
{"title":"Power Internet of Things and Its Applications [Editorial]","authors":"S. Nahavandi","doi":"10.1109/MSMC.2021.3077725","DOIUrl":"https://doi.org/10.1109/MSMC.2021.3077725","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"10 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75595775","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 : 2021-07-01DOI: 10.1109/msmc.2021.3077726
{"title":"CFP IEEE SMC 2021","authors":"","doi":"10.1109/msmc.2021.3077726","DOIUrl":"https://doi.org/10.1109/msmc.2021.3077726","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"61 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73554899","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 : 2021-07-01DOI: 10.1109/MSMC.2021.3066149
Arabinda Ghosh, Omkar Singh, A. Ray, M. Jamshidi
Variations in load demands, changes in system parameters, and the continuous integration of renewable energy sources leave scopes of improvements in the performance of a load frequency controller (LFC). To address such issues, a gravitational search algorithm (GSA)-based LFC is proposed to incorporate dynamic state variations in multiarea power systems. It helps to minimize the frequency deviations in individual areas and power deviations in the tie lines maintaining the system stability. The proposed method is validated on a two-area photovoltaic (PV) integrated thermal power system.
{"title":"A Gravitational Search Algorithm-Based Controller for Multiarea Power Systems: Conventional and Renewable Sources With Variable Load Disturbances and Perturbed System Parameters","authors":"Arabinda Ghosh, Omkar Singh, A. Ray, M. Jamshidi","doi":"10.1109/MSMC.2021.3066149","DOIUrl":"https://doi.org/10.1109/MSMC.2021.3066149","url":null,"abstract":"Variations in load demands, changes in system parameters, and the continuous integration of renewable energy sources leave scopes of improvements in the performance of a load frequency controller (LFC). To address such issues, a gravitational search algorithm (GSA)-based LFC is proposed to incorporate dynamic state variations in multiarea power systems. It helps to minimize the frequency deviations in individual areas and power deviations in the tie lines maintaining the system stability. The proposed method is validated on a two-area photovoltaic (PV) integrated thermal power system.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"1 1","pages":"20-38"},"PeriodicalIF":3.2,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76266604","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 : 2021-07-01DOI: 10.1109/msmc.2021.3077933
{"title":"2020 IEEE International Conference on Systems, Man, and Cybernetics [Society News]","authors":"","doi":"10.1109/msmc.2021.3077933","DOIUrl":"https://doi.org/10.1109/msmc.2021.3077933","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"27 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88756675","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 : 2021-04-01DOI: 10.1109/MSMC.2020.3049092
Mojtaba Kordestani, M. Saif
Demands for security, efficiency, and environmental protection have led to the rapid deployment of cyberphysical systems (CPSs), which are now an integral part of modern industries. Wireless sensor networks (WSNs), which provide distributed intelligent devices for monitoring physical and environmental conditions, are a CPS hallmark. CPSs often consist of distributed devices, such as sensors and actuators, to connect with and influence physical layer systems. Commonly, CPSs are monitored by supervisory control and data acquisition (SCADA) systems. Integrating cyber and physical worlds facilitates more effective and efficient CPS operation. However, the gains come at the price of cyberattack vulnerability.
{"title":"Observer-Based Attack Detection and Mitigation for Cyberphysical Systems: A Review","authors":"Mojtaba Kordestani, M. Saif","doi":"10.1109/MSMC.2020.3049092","DOIUrl":"https://doi.org/10.1109/MSMC.2020.3049092","url":null,"abstract":"Demands for security, efficiency, and environmental protection have led to the rapid deployment of cyberphysical systems (CPSs), which are now an integral part of modern industries. Wireless sensor networks (WSNs), which provide distributed intelligent devices for monitoring physical and environmental conditions, are a CPS hallmark. CPSs often consist of distributed devices, such as sensors and actuators, to connect with and influence physical layer systems. Commonly, CPSs are monitored by supervisory control and data acquisition (SCADA) systems. Integrating cyber and physical worlds facilitates more effective and efficient CPS operation. However, the gains come at the price of cyberattack vulnerability.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"3 1","pages":"35-60"},"PeriodicalIF":3.2,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72842791","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 : 2021-04-01DOI: 10.1109/MSMC.2020.3036378
O. Csiszár
Aggregation is the process of combining several numerical values into a single representative one, a procedure called an aggregation function. Despite the simplicity of this definition, the size of the field of its applications is incredibly huge. Making decisions (in also artificial intelligence) often leads to aggregating preferences or scores on a given set of alternatives. The concept of the ordered weighted averaging (OWA) operator, a symmetric aggregation function that allocates weights according to the input value and unifies in one operator the conjunctive and disjunctive behavior, was introduced by Yager in 1988. Since then, these functions have been axiomatized and extended in various ways. OWA operators provide a parameterized family of aggregation functions, including many of the wellknown operators. This function has attracted the interest of several researchers, and therefore, a considerable number of articles in which its properties are studied and its applications are investigated have been published. The development of an appropriate methodology for obtaining the weights is still an issue of great interest. This work provides a short review of OWA operators and gives an overview of some of the most significant results.
{"title":"Ordered Weighted Averaging Operators: A Short Review","authors":"O. Csiszár","doi":"10.1109/MSMC.2020.3036378","DOIUrl":"https://doi.org/10.1109/MSMC.2020.3036378","url":null,"abstract":"Aggregation is the process of combining several numerical values into a single representative one, a procedure called an aggregation function. Despite the simplicity of this definition, the size of the field of its applications is incredibly huge. Making decisions (in also artificial intelligence) often leads to aggregating preferences or scores on a given set of alternatives. The concept of the ordered weighted averaging (OWA) operator, a symmetric aggregation function that allocates weights according to the input value and unifies in one operator the conjunctive and disjunctive behavior, was introduced by Yager in 1988. Since then, these functions have been axiomatized and extended in various ways. OWA operators provide a parameterized family of aggregation functions, including many of the wellknown operators. This function has attracted the interest of several researchers, and therefore, a considerable number of articles in which its properties are studied and its applications are investigated have been published. The development of an appropriate methodology for obtaining the weights is still an issue of great interest. This work provides a short review of OWA operators and gives an overview of some of the most significant results.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"1 1","pages":"4-12"},"PeriodicalIF":3.2,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89530868","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 : 2021-04-01DOI: 10.1109/MSMC.2020.3036365
Ali R. Al-Roomi
Modern machine learning (ML) tools, such as artificial neural networks (ANNs) and support vector machines (SVMs), can provide highly accurate/precise predictions and estimations. However, in terms of explainability and interpretability, they are poor. To compromise between these key performance criteria, symbolic regression (SR) techniques could be used. However, they are hard to program because they have complicated mechanisms and need special optimization algorithms. The universal functions originator (UFO) is a new ML computing system that can be used in many computationbased applications. In addition to describing the variability of data sets as pure mathematical equations, this unique computing system has a very simple structure, and it can be initiated by any known optimization algorithm, including the most primitive ones, such as random search algorithms. This article introduces the UFO and shows why the system is so important to cybernetic applications.
{"title":"The Universal Functions Originator and Its Extensions: Can They Solve the Explanation Issue in Modern Machine Learning Applications?","authors":"Ali R. Al-Roomi","doi":"10.1109/MSMC.2020.3036365","DOIUrl":"https://doi.org/10.1109/MSMC.2020.3036365","url":null,"abstract":"Modern machine learning (ML) tools, such as artificial neural networks (ANNs) and support vector machines (SVMs), can provide highly accurate/precise predictions and estimations. However, in terms of explainability and interpretability, they are poor. To compromise between these key performance criteria, symbolic regression (SR) techniques could be used. However, they are hard to program because they have complicated mechanisms and need special optimization algorithms. The universal functions originator (UFO) is a new ML computing system that can be used in many computationbased applications. In addition to describing the variability of data sets as pure mathematical equations, this unique computing system has a very simple structure, and it can be initiated by any known optimization algorithm, including the most primitive ones, such as random search algorithms. This article introduces the UFO and shows why the system is so important to cybernetic applications.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"110 1","pages":"13-21"},"PeriodicalIF":3.2,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76054335","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 : 2021-04-01DOI: 10.1109/MSMC.2020.3046236
Qinghua Zhu, Jian Zhang, Yan Hou, Yan Qiao
The energy consumption of buildings is a significant responsibility, although the percentage of building energy usage varies in different countries. It is necessary to improve the energy efficiency of massive instructional buildings in universities. However, no existing attempts have been made to reduce electricity waste as well as consider student occupants' satisfaction during their study time there in the evenings. This article aims to do so due to the low utilization rate of campus classrooms for evening study. We combine students? time habits and seat selection preferences with the modified social force model to conduct simulations for occupant traffic. An improved cuckoo search (ICS) algorithm is adopted to find the threshold conditions of powering on/off classrooms, by which the schedules for classrooms can be found.
{"title":"The Energy-Saving Scheduling of Campus Classrooms: A Simulation Model","authors":"Qinghua Zhu, Jian Zhang, Yan Hou, Yan Qiao","doi":"10.1109/MSMC.2020.3046236","DOIUrl":"https://doi.org/10.1109/MSMC.2020.3046236","url":null,"abstract":"The energy consumption of buildings is a significant responsibility, although the percentage of building energy usage varies in different countries. It is necessary to improve the energy efficiency of massive instructional buildings in universities. However, no existing attempts have been made to reduce electricity waste as well as consider student occupants' satisfaction during their study time there in the evenings. This article aims to do so due to the low utilization rate of campus classrooms for evening study. We combine students? time habits and seat selection preferences with the modified social force model to conduct simulations for occupant traffic. An improved cuckoo search (ICS) algorithm is adopted to find the threshold conditions of powering on/off classrooms, by which the schedules for classrooms can be found.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"75 1","pages":"22-34"},"PeriodicalIF":3.2,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90545858","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 : 2021-04-01DOI: 10.1109/MSMC.2021.3058718
S. Nahavandi
{"title":"Applications for Machine Learning [Editorial]","authors":"S. Nahavandi","doi":"10.1109/MSMC.2021.3058718","DOIUrl":"https://doi.org/10.1109/MSMC.2021.3058718","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"1 1","pages":"3-3"},"PeriodicalIF":3.2,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78733353","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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