Electricity price forecasting is a subset of energy and power forecasting that focuses on projecting commercial electricity market present and future prices.Electricity price forecasting have been a critical input to ...Electricity price forecasting is a subset of energy and power forecasting that focuses on projecting commercial electricity market present and future prices.Electricity price forecasting have been a critical input to energy corporations’strategic decision-making systems over the last 15 years.Many strategies have been utilized for price forecasting in the past,however Artificial Intelligence Techniques(Fuzzy Logic and ANN)have proven to be more efficient than traditional techniques(Regression and Time Series).Fuzzy logic is an approach that uses membership functions(MF)and fuzzy inference model to forecast future electricity prices.Fuzzy c-means(FCM)is one of the popular clustering approach for generating fuzzy membership functions.However,the fuzzy c-means algorithm is limited to producing only one type of MFs,Gaussian MF.The generation of various fuzzy membership functions is critical since it allows for more efficient and optimal problem solutions.As a result,for the best and most improved results for electricity price forecasting,an approach to generate multiple type-1 fuzzy MFs using FCM algorithm is required.Therefore,the objective of this paper is to propose an approach for generating type-1 fuzzy triangular and trapezoidal MFs using FCM algorithm to overcome the limitations of the FCM algorithm.The approach is used to compute and improve forecasting accuracy for electricity prices,where Australian Energy Market Operator(AEMO)data is used.The results show that the proposed approach of using FCM to generate type-1 fuzzy MFs is effective and can be adopted.展开更多
Photovoltaics(PV)has been combined with many other industries,such as agriculture.But there are many problems for the sustainability of PV agriculture.Timely and accurate sustainability evaluation of modern photovolta...Photovoltaics(PV)has been combined with many other industries,such as agriculture.But there are many problems for the sustainability of PV agriculture.Timely and accurate sustainability evaluation of modern photovoltaic agriculture is of great significance for accelerating the sustainable development of modern photovoltaic agriculture.In order to improve the timeliness and accuracy of evaluation,this paper proposes an evaluation model based on interval type-2 Fuzzy AHP-TOPSIS and least squares support vector machine optimized by fireworks algorithm.Firstly,the criteria system of modern photovoltaic agriculture sustainability is constructed from three dimensions including technology sustainability,economic sustainability and social sustainability.Then,analytic hierarchy process(AHP)and technique for order preference by similarity to an ideal solution(TOPSIS)methods are improved by using interval type-2 fuzzy theory,and the traditional evaluation model based on interval type-2 Fuzzy AHP-TOPSIS is obtained,and the improved model is used for comprehensive evaluation.After that,the optimal parameters of least squares support vector machine(LSSVM)model are obtained by Fireworks algorithm(FWA)training,and the intelligent evaluationmodel for the sustainability of modern photovoltaic agriculture is constructed to realize fast and intelligent calculation.Finally,an empirical analysis is conducted to demonstrate the scientificity and accuracy of the proposed model.This study is conducive to the comprehensive evaluation of the sustainability of modern photovoltaic agriculture,and can provide decision-making support for more reasonable development model in the future of modern photovoltaic agriculture.展开更多
The important role of the concept of type-2 fuzzy point in the formation of type-2 fuzzy open sets such as type-2 fuzzy δ≈-closed?set this important role make the main objective of this paper is to...The important role of the concept of type-2 fuzzy point in the formation of type-2 fuzzy open sets such as type-2 fuzzy δ≈-closed?set this important role make the main objective of this paper is to introduce the concept type-2 fuzzy point of type-2 fuzzy set an important definitions in the composition of this concept as α≈-plane?and the support of type-2 fuzzy set after preliminaries we present the definition of type-1 fuzzy set (fuzzy set) and fuzzy point and the special concepts that helped to configure them as support.展开更多
建立了基于对称三角模糊数的多元线性回归分析模型(简记为F L R模型),利用线性规划求出中心值和模糊度。以我国1995年到2008年粮食产量(来自《中国统计年鉴2009》)为原始数据,进行了多因素模糊拟合分析。利用GM(1,N)模型对2009年至2013...建立了基于对称三角模糊数的多元线性回归分析模型(简记为F L R模型),利用线性规划求出中心值和模糊度。以我国1995年到2008年粮食产量(来自《中国统计年鉴2009》)为原始数据,进行了多因素模糊拟合分析。利用GM(1,N)模型对2009年至2013年影响我国粮食产量的5个因素指标值进行了预测,将预测值代入FLR模型求出年度粮食产量,并与2009和2010年的实际产量比较,表明这种GM(1,N)模型和FLR模型有机结合形成的复合模型,预测精度高,可操作性强,且具有很高的可信度。展开更多
This article introduces a singleton type-1 fuzzy logic system(T1-SFLS) controller and Fuzzy-WDO hybrid for the autonomous mobile robot navigation and collision avoidance in an unknown static and dynamic environment. T...This article introduces a singleton type-1 fuzzy logic system(T1-SFLS) controller and Fuzzy-WDO hybrid for the autonomous mobile robot navigation and collision avoidance in an unknown static and dynamic environment. The WDO(Wind Driven Optimization) algorithm is used to optimize and tune the input/output membership function parameters of the fuzzy controller. The WDO algorithm is working based on the atmospheric motion of infinitesimal small air parcels navigates over an N-dimensional search domain. The performance of this proposed technique has compared through many computer simulations and real-time experiments by using Khepera-Ⅲ mobile robot. As compared to the T1-SFLS controller the Fuzzy-WDO algorithm is found good agreement for mobile robot navigation.展开更多
As per World Health Organization report which was released in the year of 2019,Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabete...As per World Health Organization report which was released in the year of 2019,Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabetes all over the world.Hence it is inferred that diabetes is rampant across the world with the majority of the world population being affected by it.Among the diabetics,it can be observed that a large number of people had failed to identify their disease in the initial stage itself and hence the disease level moved from Type-1 to Type-2.To avoid this situation,we propose a new fuzzy logic based neural classifier for early detection of diabetes.A set of new neuro-fuzzy rules is introduced with time constraints that are applied for thefirst level classification.These levels are further refined by using the Fuzzy Cognitive Maps(FCM)with time intervals for making thefinal decision over the classification process.The main objective of this proposed model is to detect the diabetes level based on the time.Also,the set of neuro-fuzzy rules are used for selecting the most contributing values over the decision-making process in diabetes prediction.The proposed model proved its efficiency in performance after experiments conducted not only from the repository but also by using the standard diabetic detection models that are available in the market.展开更多
For short-term wind power forecasting,an interval A2-C1 type-2(IT2)Takagi-Sugeno-Kang(TSK)fuzzy logic system(FLS)method(“A”means antecedent and“C”consequent)based on an extended Kalman filter(EKF)optimization algo...For short-term wind power forecasting,an interval A2-C1 type-2(IT2)Takagi-Sugeno-Kang(TSK)fuzzy logic system(FLS)method(“A”means antecedent and“C”consequent)based on an extended Kalman filter(EKF)optimization algorithm is proposed.Compared with the type-1(T1)FLS model,the IT2 TSK FLS method can simultaneously model both intra-and inter-individual uncertainty and further optimize the antecedent and consequent parameters using the EKF to improve forecasting performance further.The proposed IT2 A2-C1 FLS method is applied to Mackey-Glass chaotic time series and wind power forecasting instances in a certain region,under the same conditions.It is also compared with the T1 TSK FLS and IT2 TSK FLS methods with back propagation(BP)and particle swarm optimization(PSO)algorithms,as well as IT2 A2-C0 TSK FLS methods with EKF.The experimental results confirm that the proposed IT2 A2-C1 FLS method is superior to the other FLS methods regarding performance,which demonstrates its effectiveness and application potential.展开更多
In this paper,we define the basic concept of triangular neutrosophic cubic hesitant fuzzy number and their properties.We develop a triangular neutrosophic cubic hesitant fuzzy ordered weighted arithmetic averaging (TN...In this paper,we define the basic concept of triangular neutrosophic cubic hesitant fuzzy number and their properties.We develop a triangular neutrosophic cubic hesitant fuzzy ordered weighted arithmetic averaging (TNCIIFOWAA) operator and a triangular neu-trosophic cubic hesitant fuzzy ordered weighted geometric averaging (TNCIIFOWGA) operator to aggregate triangular neutrosophic cubic hesitant fuzzy number (TNCHFN) information and investigate their properties.Furthermore,a multiple attribute decision-making method based on the TNCHFOWAA operator and triangular neutrosophic cubic hesitant fuzzy ordered weighted geometric (TNCHFOWG) operator and the score function of TNCHFN is established under a TNCHFN environment.Finally,an illustrative example of investment alternatives is given to demonstrate the application and effec-tiveness of the developed approach.展开更多
基金This research is an ongoing research supported by Yayasan UTP Grant(015LC0-321&015LC0-311)Fundamental Research Grant Scheme(FRGS/1/2018/ICT02/UTP/02/1)a grant funded by the Ministry of Higher Education,Malaysia.
文摘Electricity price forecasting is a subset of energy and power forecasting that focuses on projecting commercial electricity market present and future prices.Electricity price forecasting have been a critical input to energy corporations’strategic decision-making systems over the last 15 years.Many strategies have been utilized for price forecasting in the past,however Artificial Intelligence Techniques(Fuzzy Logic and ANN)have proven to be more efficient than traditional techniques(Regression and Time Series).Fuzzy logic is an approach that uses membership functions(MF)and fuzzy inference model to forecast future electricity prices.Fuzzy c-means(FCM)is one of the popular clustering approach for generating fuzzy membership functions.However,the fuzzy c-means algorithm is limited to producing only one type of MFs,Gaussian MF.The generation of various fuzzy membership functions is critical since it allows for more efficient and optimal problem solutions.As a result,for the best and most improved results for electricity price forecasting,an approach to generate multiple type-1 fuzzy MFs using FCM algorithm is required.Therefore,the objective of this paper is to propose an approach for generating type-1 fuzzy triangular and trapezoidal MFs using FCM algorithm to overcome the limitations of the FCM algorithm.The approach is used to compute and improve forecasting accuracy for electricity prices,where Australian Energy Market Operator(AEMO)data is used.The results show that the proposed approach of using FCM to generate type-1 fuzzy MFs is effective and can be adopted.
基金This work is supported by Humanities and Social Science Research Project of Hebei Education Department,China(No.SD2021044)Graduate Demonstration Course Construction Project of Hebei Province,China(No.KCJSX2021091).
文摘Photovoltaics(PV)has been combined with many other industries,such as agriculture.But there are many problems for the sustainability of PV agriculture.Timely and accurate sustainability evaluation of modern photovoltaic agriculture is of great significance for accelerating the sustainable development of modern photovoltaic agriculture.In order to improve the timeliness and accuracy of evaluation,this paper proposes an evaluation model based on interval type-2 Fuzzy AHP-TOPSIS and least squares support vector machine optimized by fireworks algorithm.Firstly,the criteria system of modern photovoltaic agriculture sustainability is constructed from three dimensions including technology sustainability,economic sustainability and social sustainability.Then,analytic hierarchy process(AHP)and technique for order preference by similarity to an ideal solution(TOPSIS)methods are improved by using interval type-2 fuzzy theory,and the traditional evaluation model based on interval type-2 Fuzzy AHP-TOPSIS is obtained,and the improved model is used for comprehensive evaluation.After that,the optimal parameters of least squares support vector machine(LSSVM)model are obtained by Fireworks algorithm(FWA)training,and the intelligent evaluationmodel for the sustainability of modern photovoltaic agriculture is constructed to realize fast and intelligent calculation.Finally,an empirical analysis is conducted to demonstrate the scientificity and accuracy of the proposed model.This study is conducive to the comprehensive evaluation of the sustainability of modern photovoltaic agriculture,and can provide decision-making support for more reasonable development model in the future of modern photovoltaic agriculture.
文摘The important role of the concept of type-2 fuzzy point in the formation of type-2 fuzzy open sets such as type-2 fuzzy δ≈-closed?set this important role make the main objective of this paper is to introduce the concept type-2 fuzzy point of type-2 fuzzy set an important definitions in the composition of this concept as α≈-plane?and the support of type-2 fuzzy set after preliminaries we present the definition of type-1 fuzzy set (fuzzy set) and fuzzy point and the special concepts that helped to configure them as support.
文摘建立了基于对称三角模糊数的多元线性回归分析模型(简记为F L R模型),利用线性规划求出中心值和模糊度。以我国1995年到2008年粮食产量(来自《中国统计年鉴2009》)为原始数据,进行了多因素模糊拟合分析。利用GM(1,N)模型对2009年至2013年影响我国粮食产量的5个因素指标值进行了预测,将预测值代入FLR模型求出年度粮食产量,并与2009和2010年的实际产量比较,表明这种GM(1,N)模型和FLR模型有机结合形成的复合模型,预测精度高,可操作性强,且具有很高的可信度。
文摘This article introduces a singleton type-1 fuzzy logic system(T1-SFLS) controller and Fuzzy-WDO hybrid for the autonomous mobile robot navigation and collision avoidance in an unknown static and dynamic environment. The WDO(Wind Driven Optimization) algorithm is used to optimize and tune the input/output membership function parameters of the fuzzy controller. The WDO algorithm is working based on the atmospheric motion of infinitesimal small air parcels navigates over an N-dimensional search domain. The performance of this proposed technique has compared through many computer simulations and real-time experiments by using Khepera-Ⅲ mobile robot. As compared to the T1-SFLS controller the Fuzzy-WDO algorithm is found good agreement for mobile robot navigation.
文摘As per World Health Organization report which was released in the year of 2019,Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabetes all over the world.Hence it is inferred that diabetes is rampant across the world with the majority of the world population being affected by it.Among the diabetics,it can be observed that a large number of people had failed to identify their disease in the initial stage itself and hence the disease level moved from Type-1 to Type-2.To avoid this situation,we propose a new fuzzy logic based neural classifier for early detection of diabetes.A set of new neuro-fuzzy rules is introduced with time constraints that are applied for thefirst level classification.These levels are further refined by using the Fuzzy Cognitive Maps(FCM)with time intervals for making thefinal decision over the classification process.The main objective of this proposed model is to detect the diabetes level based on the time.Also,the set of neuro-fuzzy rules are used for selecting the most contributing values over the decision-making process in diabetes prediction.The proposed model proved its efficiency in performance after experiments conducted not only from the repository but also by using the standard diabetic detection models that are available in the market.
基金Supported by the Key Project of Natural Science Foundation of Gansu Province(25JRRA150)the Gansu Provincial Natural Science Foundation(23JRRA876).
文摘For short-term wind power forecasting,an interval A2-C1 type-2(IT2)Takagi-Sugeno-Kang(TSK)fuzzy logic system(FLS)method(“A”means antecedent and“C”consequent)based on an extended Kalman filter(EKF)optimization algorithm is proposed.Compared with the type-1(T1)FLS model,the IT2 TSK FLS method can simultaneously model both intra-and inter-individual uncertainty and further optimize the antecedent and consequent parameters using the EKF to improve forecasting performance further.The proposed IT2 A2-C1 FLS method is applied to Mackey-Glass chaotic time series and wind power forecasting instances in a certain region,under the same conditions.It is also compared with the T1 TSK FLS and IT2 TSK FLS methods with back propagation(BP)and particle swarm optimization(PSO)algorithms,as well as IT2 A2-C0 TSK FLS methods with EKF.The experimental results confirm that the proposed IT2 A2-C1 FLS method is superior to the other FLS methods regarding performance,which demonstrates its effectiveness and application potential.
文摘In this paper,we define the basic concept of triangular neutrosophic cubic hesitant fuzzy number and their properties.We develop a triangular neutrosophic cubic hesitant fuzzy ordered weighted arithmetic averaging (TNCIIFOWAA) operator and a triangular neu-trosophic cubic hesitant fuzzy ordered weighted geometric averaging (TNCIIFOWGA) operator to aggregate triangular neutrosophic cubic hesitant fuzzy number (TNCHFN) information and investigate their properties.Furthermore,a multiple attribute decision-making method based on the TNCHFOWAA operator and triangular neutrosophic cubic hesitant fuzzy ordered weighted geometric (TNCHFOWG) operator and the score function of TNCHFN is established under a TNCHFN environment.Finally,an illustrative example of investment alternatives is given to demonstrate the application and effec-tiveness of the developed approach.
