Search Results - (( using evolutionary study algorithm ) OR ( using optimization based algorithm ))

Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

Get full text
Get full text
Get full text
Get full text

Multi-objective optimization of all-wheel drive electric formula vehicle for performance and energy efficiency using evolutionary algorithms by Tey, Jing Yuen, Ramli, Rahizar

“…A new method based on constraint multi-objective optimization using evolutionary algorithms is proposed to optimize the powertrain design of a battery electric formula vehicle with an all-wheel independent motor drive. …”
Get full text
Get full text

Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: Foundations, Methods, and Applications reveals the potential of innovative optimization algorithms to support sustainability in modern energy systems. …”
Get full text
Get full text
Get full text

A Multi-objective Evolutionary Algorithm Based On Decomposition For Continuous Optimization Using A Step-function Technique by Chuah, How Siang

Get full text
Get full text

A comprehensive comparison of evolutionary optimization limited by number of evaluations against time constraints by Jia, Hui Ong, Teo, Jason Tze Wi

“…Practically allevolutionary optimization studies have focused exclusively on the use of number of fitness evaluations as the constraining factor when comparing different evolutionary algorithms (EAs). …”
Get full text
Get full text
Get full text
Get full text

Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…To show the effectiveness of EMA-DL, comparison studies were conducted among other metaheuristic optimizers that were also used to optimize the DL parameters viz, Particles Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE) as well as the Adaptive Moment Estimation (ADAM). …”
Get full text
Get full text
Get full text
Get full text

Evaluation of fast evolutionary programming, firefly algorithm and mutate-cuckoo search algorithm in single-objective optimization / Muhammad Zakyizzuddin Rosselan, Shahril Irwan S... by Rosselan, Muhammad Zakyizzuddin, Sulaiman, Shahril Irwan, Othman, Norhalida

“…In this study proposes an evaluation of different computational intelligences, i.e Fast-Evolutionary Algorithm (FEP), Firefly Algorithm (FA) and Mutate-cuckoo Search Algorithm (MCSA) for solving single-objective optimization problem. …”
Get full text
Get full text
Get full text

Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems by Yousefi M., Darus A.N., Yousefi M., Hooshyar D.

Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

“…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
Get full text
Get full text
Get full text

Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

“…The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
Get full text
Get full text
Get full text

Evolutionary mating algorithm by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Hamdan, Daniyal, Mirjalili, Seyedali

“…This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve constrained optimization problems. …”
Get full text
Get full text
Get full text
Get full text

Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

“…The primary objectives were to assess the performance of three evolutionary algorithms ? Heap-Based Optimizer (HBO), Multiverse Optimizer (MVO), and Whale Optimization Algorithm (WOA) ? …”

Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

“…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
Get full text
Get full text
Get full text

Hybrid evolutionary-dolphin echolocation programming for sizing optimization of stand-alone photovoltaic systems / Zulkifli Othman by Othman, Zulkifli

“…Initially, Iterative-based Sizing Algorithm (ISA) which uses the non-computational intelligence-based approach is presented to serve as the benchmark for computational intelligence (CI)-based sizing algorithm. …”
Get full text
Get full text

Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty by Ehteram, Mohammad, Mousavi, Sayed Farhad, Karami, Hojat, Farzin, Saeed, Singh, Vijay P., Chau, Kwok Wing, El-Shafie, Ahmed

“…Results showed the volume of water to be released for the future period, based on all evolutionary algorithms used, was less than for the base period, and the bat algorithm with high-reliability index and low vulnerability index performed better among other evolutionary algorithms.…”
Get full text
Get full text

Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering by Rashed, Alwatben Batoul

“…Evolutionary algorithms have been extensively used to resolve problems associated with multiple and often conflicting objectives. …”
Get full text
Get full text

Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

“…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
Get full text
Get full text

Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm by Mohd Redzuan, Ahmad, Ismail, Musirin, M. M., Othman

Get full text
Get full text
Get full text

Evolutionary multi-objective optimization of autonomous mobile robots in neural-based cognition for behavioural robustness by Chin, Kim On, Teo, Jason Tze Wi, Azali Saudi

“…The utilization of a multi-objective approach for evolving artificial neural networks that act as the controllers for phototaxis and radio frequency (RF) localization behaviors of a virtual Khepera robot simulated in a 3D, physics-based environment is discussed in this chapter. It explains the comparison performances among the elitism without archive and elitism with archive used in the evolutionary multi-objective optimization (EMO) algorithm in an evolutionary robotics study. …”
Get full text
Get full text
Get full text

Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
Get full text
Get full text
Get full text