Hybrid particle filter–particle swarm optimization algorithm and application to fuzzy controlled servo systems
This article presents a hybrid metaheuristic optimization algorithm that combines particle
filter (PF) and particle swarm optimization (PSO) algorithms. The new PF–PSO algorithm …
filter (PF) and particle swarm optimization (PSO) algorithms. The new PF–PSO algorithm …
Optimal tuning of interval type-2 fuzzy controllers for nonlinear servo systems using Slime Mould Algorithm
This paper presents a novel application of the metaheuristic Slime Mould Algorithm (SMA) to
the optimal tuning of interval type-2 fuzzy controllers. Inserting the information feedback …
the optimal tuning of interval type-2 fuzzy controllers. Inserting the information feedback …
Slime mould algorithm-based tuning of cost-effective fuzzy controllers for servo systems
This paper suggests five new contributions with respect to the state-of-the-art. First, the
optimal tuning of cost-effective fuzzy controllers represented by Takagi–Sugeno–Kang …
optimal tuning of cost-effective fuzzy controllers represented by Takagi–Sugeno–Kang …
Tensor product‐based model transformation approach to tower crane systems modeling
This paper presents the application of the tensor product (TP)‐based model transformation
approach to produce Tower CRrane (TCR) systems models. The modeling approach starts …
approach to produce Tower CRrane (TCR) systems models. The modeling approach starts …
Boosting quantum rotation gate embedded slime mould algorithm
The slime mould algorithm is an interesting swarm-based algorithm proposed in 2020 based
on this entity's trajectory finding abilities in nature. It simulates slime mould movement …
on this entity's trajectory finding abilities in nature. It simulates slime mould movement …
EnLSTM-WPEO: Short-term traffic flow prediction by ensemble LSTM, NNCT weight integration, and population extremal optimization
Accurate and stable short-term traffic flow prediction is an indispensable part in current
intelligent transportation systems. In this paper, a novel short-term traffic flow forecasting …
intelligent transportation systems. In this paper, a novel short-term traffic flow forecasting …
An adaptive deep reinforcement learning approach for MIMO PID control of mobile robots
Intelligent control systems are being developed for the control of plants with complex
dynamics. However, the simplicity of the PID (proportional–integrative–derivative) controller …
dynamics. However, the simplicity of the PID (proportional–integrative–derivative) controller …
Review of the research landscape of multi-criteria evaluation and benchmarking processes for many-objective optimization methods: coherent taxonomy, challenges …
RT Mohammed, R Yaakob, AA Zaidan… - … Journal of Information …, 2020 - World Scientific
Evaluation and benchmarking of many-objective optimization (MaOO) methods are
complicated. The rapid development of new optimization algorithms for solving problems …
complicated. The rapid development of new optimization algorithms for solving problems …
A hybrid renewable-based solution to electricity and freshwater problems in the off-grid Sundarbans region of India: Optimum sizing and socio-enviro-economic …
Stand-alone hybrid renewable energy systems have been proven as a promising pathway
towards reliable and sustainable electrification of remote rural off-grid communities. The …
towards reliable and sustainable electrification of remote rural off-grid communities. The …
Dealing with multi-modality using synthesis of Moth-flame optimizer with sine cosine mechanisms
Evolutionary population-based methods have found their applications in dealing with many
real-world simulation experiments and mathematical modelling problems. The Moth-flame …
real-world simulation experiments and mathematical modelling problems. The Moth-flame …