Search Results - (( model relation between algorithm ) OR ( swarm optimization ((max algorithm) OR (_ algorithm)) ))

A particle swarm optimization and min-max­-based workflow scheduling algorithm with QoS satisfaction for service-­oriented grids by Ambursa, Faruku Umar, Latip, Rohaya, Abdullah, Azizol, K. Subramaniam, Shamala

“…It also outperforms the comparison algorithm, with about 30% increase, in terms of cumulative QoS satisfaction of optimization requirements. …”
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Performance comparison of differential evolution and particle swarm optimization in constrained optimization by Iwan, Mahmud, Akmeliawati, Rini, Faisal, Tarig, Al-Assadi, Hayder M.A.A.

“…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm by Faisal, Ali Raed, Hashim, Fazirulhisyam, Ismail, Mahamod, Noordin, Nor Kamariah

“…However, achieving equivalent backhaul reduction based on limited feedback channel state information is challenging when linear techniques, such as zero-forcing beamforming (BF) are used, which led to the use of stochastic algorithms instead. Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). …”
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Artificial neural network-salp-swarm algorithm for stock price prediction by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan, Abdul Aziz

“…Additionally, the SSA-ANN model is compared with other two hybrid models: the ANN optimized by the Whale Optimization Algorithm (WOA-ANN) and Moth-Flame Optimizer (MOA-ANN), as well as a single model, namely the Autoregressive Integrated Moving Average (ARIMA). …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

“…Friedman test using GRG metric shows significant better performance (p-values<0.05) for PACS algorithm compared to benchmark algorithms. The proposed models and algorithm can be used to solve the multi-objective GMS problem while the new parameters’ values can be used to obtain optimal or near optimal maintenance scheduling of generators. …”
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Interacted Multiple Ant Colonies for Search Stagnation Problem by Aljanabi, Alaa Ismael

“…Ant Colony Optimization (ACO) is a successful application of swarm intelligence. …”
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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

“…Improved mean fitness function values were also revealed in the TRS (11.63%) and EMPS (69.63%) assessments, surpassing the conventional algorithm. This proposed algorithm produced solutions with superior accuracy and consistency compared to various established metaheuristic strategies, including particle swarm optimizer, grey wolf optimizer, multi-verse optimizer, AOA, and a hybrid optimizer (average multi-verse optimizer-sine-cosine algorithm).…”
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Recent advances of whale optimization algorithm, its versions and applications by Alyasseri Z.A.A., Ali N.S., Al-Betar M.A., Makhadmeh S.N., Jamil N., Awadallah M.A., Braik M., Mirjalili S.

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A comprehensive overview of PSO-LSTM approaches: Applications, analytical insights, and future opportunities by Hosseinzadeh, Mehdi, Tanveer, Jawad, Rahmani, Amir Masoud, Gharehchopogh, Farhad Soleimanian, Mohd Yusof, Norfadzlia, Khoshvaght, Parisa, Zhe, Liu, Porntaveetus, Thantrira, Lee, Sang-Woong

“…The combination of particle swarm optimization algorithm with long short-term memory has led to new horizons in data analysis and solving complex problems. …”
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Structural optimization of 4-DOF agricultural robot arm by Nurul Emylia Natasya Ahmad Zakey, Mohd Hairi Mohd Zaman, Mohd Faisal Ibrahim

“…Simulation of kinematic modeling is performed using MATLAB software. This study studies various optimization algorithms to compare the performance of algorithms that can achieve the optimal length with minimum errors. …”
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A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function by Mahdi, F.P., Vasant, P., Abdullah-Al-Wadud, M., Watada, J., Kallimani, V.

“…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function by Mahdi, F.P., Vasant, P., Abdullah-Al-Wadud, M., Watada, J., Kallimani, V.

“…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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Particle Swarm Optimization (PMO) Algorithm With Reduced Number Of Switches In Multilevel Inverter (MLI) by Al-Hiealy, Mohammed Rasheed Jubair, Omar, Rosli, Sulaiman, Marizan, Abd Halim, Wahidah

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A review of the hybrid artificial intelligence and optimization modelling of hydrological streamflow forecasting by Ibrahim K.S.M.H., Huang Y.F., Ahmed A.N., Koo C.H., El-Shafie A.

“…Climate change; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Hydrology; Particle swarm optimization (PSO); Reservoirs (water); Stream flow; Support vector machines; Water supply systems; Adaptive neuro-fuzzy inference system; Artificial bee colony; Artificial neural network; Genetic algorithm; Intelligence modeling; Optimization algorithms; Particle swarm optimization; Reservoir inflow; Streamflow forecasting; Support vector machine; Forecasting…”

A Systematic Review of Metaheuristic Algorithms in Human Activity Recognition : Applications, Trends, and Challenges by John Deutero, Kisoi, Norfadzlan, Yusup, Syahrul Nizam, Junaini

“…Metaheuristic algorithms have emerged as promising techniques for optimizing human activity recognition (HAR) systems. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Ahmad Salihin, Samsudin, Amir Izzani, Mohamed, Mohd Mawardi, Saari

“…A comprehensive data preprocessing pipeline was implemented, including missing value treatment, outlier removal, and feature normalization using Min-Max scaling. Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization by M. F. F., Ab Rashid, Ahmad Nasser, Mohd Rose, N. M. Zuki, N. M.

“…The results were also compared with relatively recent algorithm such as Whale Optimization Algorithm and Harris Haws Optimization. …”
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Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., Sherif M., El-Shafie A.

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Metaheuristic algorithms for solving lot-sizing and scheduling problems in single and multi-plant environments / Maryam Mohammadi by Mohammadi, Maryam

“…Numerical examples are presented to illustrate the effectiveness and efficiency of the proposed models. Metaheuristic approaches namely genetic algorithm, particle swarm optimization, artificial bee colony, simulated annealing, and imperialist competitive algorithm are adopted for the optimization procedures. …”
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