Search Results - (( model evaluation _ algorithm ) OR ( based optimization strategy algorithm ))*

Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

“…A multi-objective PACS algorithm based on sequential strategy which considers unit commitment and GMS problem separately is proposed to obtain solution for a proposed GMS model. …”
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

“…Compared with the traditional credit evaluation model, PSOEBGWO-CatBoost has better accuracy and practical application value.…”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques by Lipu M.S.H., Hussain A., Saad M.H.M., Hannan M.A.

Optimization of operations of reservoir systems for hydropower generation in Tigris River Basin, Iraq by Al-Aqeel, Yousif Hashim Abdullah

“…The performances of these two algorithms were evaluated through comparing their optimal values. …”
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms by Almubaidin M.A., Ahmed A.N., Sidek L.M., AL-Assifeh K.A.H., El-Shafie A.

“…This involves their application to various facets of the reservoir operating system, particularly in determining optimal rule curves. This study delves into the exploration of different algorithms, including Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Firefly Algorithm (FA), Invasive Weed Optimization (IWO), Teaching Learning-Based Optimization (TLBO), and Harmony Search (HS). …”

Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling by Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Abd Aziz, Nor Azlina, Ibrahim, Zuwairie, Mubin, Marizan, Nawawi, Sophan Wahyudi, Mohamad, Mohd Saberi

“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection by Iqbal, Muhammad

“…Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. …”
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Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Ab. Aziz, Nor Azlina, Ibrahim, Zuwairie, Mubin, Marizan, Nawawi, Sophan Wahyudi, Mohamad, Mohd Saberi

“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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A comparative study for parameter selection in online auctions by Gan, Kim Soon

“…Hence, this work attempts to improve an existing bidding strategy by taking into accounts the evolution of various model of generic algorithm in optimizing the parameter of the bidding strategies. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

“…The HM emerges as a dominant strategy, driven by the Multi-Objective Differential Evolution (MODE) algorithm under literature-based control parameter settings for the mathematical model. …”
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Optimizing tree planting areas through integer programming and improved genetic algorithm by Md Badarudin, Ismadi

“…With the aim of evaluating the algorithm efficiency, comparisons between the proposed strategies and the previous strategies were conducted. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…Therefore, this article identified various continuous-time Hammerstein models based on an improved Archimedes optimization algorithm (IAOA) to address these concerns. …”
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Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Marizan, Mubin, Sophan Wahyudi, Nawawi, Mohd Saberi, Mohamad

“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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Experimental Model for Teaching Software Testing by Kamal Z., Zamli, Hasneeza, L. Zakaria

“…The EMTST framework is explained in details and along with the comparison of MBO algorithm with other pairwise strategies. In conclusion, this strategy with MBO can help students understand the concept and practical aspect of the development of a pairwise strategy and how to evaluate the effectiveness of the algorithm in AI-based pairwise strategy.…”
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A Hybrid Neural Network-Based Improved PSO Algorithm for Gas Turbine Emissions Prediction by Yousif S.T., Ismail F.B., Al-Bazi A.

“…This study proposes a hybrid model integrating the Feed forward Neural Network (FFNN) model and Particle Swarm Optimization (PSO) algorithm to predict gas emissions from natural gas power plants. …”

Enhancing NoC-based MPSoC performance: a predictive approach with ANN and guaranteed convergence arithmetic optimization algorithm by Muhsen, Yousif Raad, Husin, Nor Azura, Zolkepli, Maslina, Manshor, Noridayu, Al-Hchaimi, Ahmed Abbas Jasim, Ridha, Hussein Mohammed

“…The main idea of the proposed method is to develop a prediction model, speci‚cally an Arti‚cial Neural Network (ANN) optimized using the Guaranteed Convergence Arithmetic Optimization Algorithm (GCAOA-ANN), for predicting the utilized routing algorithm in NoC-based MPSoC platform during the DSE process. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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