Purpose–The purpose of this paper is to propose distributed learning-based three different metaheuristic algorithms for the identification of nonlinear systems.The proposed algorithms are experimented in this study t...Purpose–The purpose of this paper is to propose distributed learning-based three different metaheuristic algorithms for the identification of nonlinear systems.The proposed algorithms are experimented in this study to address problems for which input data are available at different geographic locations.In addition,the models are tested for nonlinear systems with different noise conditions.In a nutshell,the suggested model aims to handle voluminous data with low communication overhead compared to traditional centralized processing methodologies.Design/methodology/approach–Population-based evolutionary algorithms such as genetic algorithm(GA),particle swarm optimization(PSO)and cat swarm optimization(CSO)are implemented in a distributed form to address the system identification problem having distributed input data.Out of different distributed approaches mentioned in the literature,the study has considered incremental and diffusion strategies.Findings–Performances of the proposed distributed learning-based algorithms are compared for different noise conditions.The experimental results indicate that CSO performs better compared to GA and PSO at all noise strengths with respect to accuracy and error convergence rate,but incremental CSO is slightly superior to diffusion CSO.Originality/value–This paper employs evolutionary algorithms using distributed learning strategies and applies these algorithms for the identification of unknown systems.Very few existing studies have been reported in which these distributed learning strategies are experimented for the parameter estimation task.展开更多
In daily life,children often get used to staying late or even staying up late because of the rebellion of adolescent psychology against the non-mandatory rules formulated by the family.To explore the legal effect of s...In daily life,children often get used to staying late or even staying up late because of the rebellion of adolescent psychology against the non-mandatory rules formulated by the family.To explore the legal effect of such rules,this article analyzes the regulation of bedtime according to customary law.The two criteria of discretion and strategic non-enforcement are used to support the reason why customary laws(incorporate the bedtime rule made by the parents)have real legal effects.Through legal case studies and the comparison and contraction of disobeying regulated bedtime,the author admits that such rules sometimes can be criticized,which jeopardizes the characteristics of enforcement and credibility for laws with certain unfairness and lack of enforcement.However,they can be refuted based on the progressive principle,the dynamic balance between rules and discretion,and another theoretical basis.Given the disputes raised in this paper,the author also put forward the corresponding improvement measures after each refutation.To put it in a nutshell,the author thinks that the family rules produced in the absence of hard punishment like the regulated bedtime.展开更多
文摘Purpose–The purpose of this paper is to propose distributed learning-based three different metaheuristic algorithms for the identification of nonlinear systems.The proposed algorithms are experimented in this study to address problems for which input data are available at different geographic locations.In addition,the models are tested for nonlinear systems with different noise conditions.In a nutshell,the suggested model aims to handle voluminous data with low communication overhead compared to traditional centralized processing methodologies.Design/methodology/approach–Population-based evolutionary algorithms such as genetic algorithm(GA),particle swarm optimization(PSO)and cat swarm optimization(CSO)are implemented in a distributed form to address the system identification problem having distributed input data.Out of different distributed approaches mentioned in the literature,the study has considered incremental and diffusion strategies.Findings–Performances of the proposed distributed learning-based algorithms are compared for different noise conditions.The experimental results indicate that CSO performs better compared to GA and PSO at all noise strengths with respect to accuracy and error convergence rate,but incremental CSO is slightly superior to diffusion CSO.Originality/value–This paper employs evolutionary algorithms using distributed learning strategies and applies these algorithms for the identification of unknown systems.Very few existing studies have been reported in which these distributed learning strategies are experimented for the parameter estimation task.
文摘In daily life,children often get used to staying late or even staying up late because of the rebellion of adolescent psychology against the non-mandatory rules formulated by the family.To explore the legal effect of such rules,this article analyzes the regulation of bedtime according to customary law.The two criteria of discretion and strategic non-enforcement are used to support the reason why customary laws(incorporate the bedtime rule made by the parents)have real legal effects.Through legal case studies and the comparison and contraction of disobeying regulated bedtime,the author admits that such rules sometimes can be criticized,which jeopardizes the characteristics of enforcement and credibility for laws with certain unfairness and lack of enforcement.However,they can be refuted based on the progressive principle,the dynamic balance between rules and discretion,and another theoretical basis.Given the disputes raised in this paper,the author also put forward the corresponding improvement measures after each refutation.To put it in a nutshell,the author thinks that the family rules produced in the absence of hard punishment like the regulated bedtime.
