Search Results - (( based evaluation _ algorithm ) OR ( rate optimization based algorithm ))*
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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An enhanced opposition-based firefly algorithm for solving complex optimization problems
Published 2014“…Firefl y algorithm is one of the heuristic optimization algorithms which mainly based on the light intensity and the attractiveness of fi refl y. …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…A new meta-heuristic optimization technique called the Slime Mould Algorithm (SMA) approach has a high convergence rate or a few iterations and superior optimization indices analyzed against other algorithms. …”
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An enhanced metaheuristic approach to solve quadratic assignment problem using hybrid technique
Published 2021“…The valuate of performance HDDETS algorithm comparison to existing hybrid-based algorithms, namely: Biogeography-Based Optimization Tabu Search (BBOTS), Whale Algorithm with Tabu Search (WAITS), Hybrid Ant System (HAS), Lexisearch and Genetic Algorithms (LSGA), and Golden Ball Simulated Annealing (GBSA) algorithms. …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…The experimentally, the PMT shows promising results by accelerating the convergence rate against the original algorithms with the same number of fitness evaluations.…”
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Enhancing three variants of harmony search algorithm for continuous optimization problems
Published 2021“…Meanwhile, opposition-based learning (OBL), is an effective technique used to improve the performance of different optimization algorithms, including HS. …”
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An enhanced ant colony system algorithm for dynamic fault tolerance in grid computing
Published 2020“…The proposed algorithm was developed in a simulated grid environment called GridSim and evaluated against other fault tolerance algorithms such as trust-based ACO, fault tolerance ACO, ACO without fault tolerance and ACO with fault tolerance in terms of total execution time, average latency, average makespan, throughput, execution success rate and load balancing. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…To evaluate the performance of the proposed IBOA training method, the obtained results are compared to the results of the momentum backpropagation (MBP), the particle swarm optimization (PSO) and the standard butterfly optimization algorithm (BOA) training methods. …”
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Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods
Published 2021“…The evaluation criteria of Many Objective Optimization algorithm (MaOO) play a critical role in evaluating the competition MaOO algorithms. …”
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Modified Opposition Based Learning to Improve Harmony Search Variants Exploration
Published 2020“…Opposition-based learning variants enhanced the explorations and help optimization algorithms to avoid local optima falling. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA)
Published 2021“…The proposed Hybrid Sentiment-based Support Vector Machine with a Whale Optimization Algorithm (SVMWOA). will be evaluated and compared based on performance measures. …”
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Proceeding Paper -
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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15
Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning
Published 2019“…Two HS parameters were automatically updated using GWO, namely, pitch adjustment rate and bandwidth. The proposed hybrid algorithm for global optimization problems is called GWO-HS. …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
Published 2024“…The proposed algorithm updates the learning rate in every iteration based on the approximated spectrum of the Hessian of the loss function. …”
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Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
Published 2020“…Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. …”
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Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging
Published 2016“…However, their performances are not well optimized. This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. …”
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