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  1. 1
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
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  2. 2
    Multi-objective scientific workflow scheduling algorithm in multi-cloud environment for satisfying QoS requirements

    Multi-objective scientific workflow scheduling algorithm in multi-cloud environment for satisfying QoS requirements by Ramadhan, Mazen Farid Ebrahim

    Published 2022
    “…Second, to propose a minimum-weight-based multi-objective algorithm (MOS-MWO), which is based on Particle Swarm Optimization (PSO) technique and a novel minimum weight optimization approach, that improves user’s QoS satisfaction. …”
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  3. 3
    Fuzzy clustering method and evaluation based on multi criteria decision making technique

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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  4. 4
    Optimizing dam and reservoir operations using machine learning

    Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

    Published 2025
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  5. 5
    Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk

    Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk by Zhang, H., Watada, J., Wang, B.

    Published 2019
    “…In addition, compared with the VaR-FMOPSM model, our sensitivity-based improved model with the IPSO algorithm also performs better than Genetic Algorithm and Simulate Anneal Algorithm (SA), it provides the same performance on this point. …”
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  6. 6
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Noor Akma Ibrahim, Abdul Kudus, Isa Daud, Mohd. Rizam Abu Bakar

    Published 2009
    “…Five cutpoint determination methods are developed based on regression of competing risks subdistribution. …”
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  7. 7
    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio

    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

    Published 2018
    “…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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  8. 8
    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio

    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

    Published 2018
    “…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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  9. 9
    Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH

    Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

    Published 2021
    “…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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  10. 10
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Ibrahim, Noor Akma, Kudus, Abdul, Daud, Isa, Abu Bakar, Mohd Rizam

    Published 2009
    “…Five cutpoint determination methods are developed based on regression of competing risks subdistribution. …”
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  11. 11
    Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods

    Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

    Published 2017
    “…The reliability assessment of the adequacy of the generating system is normally calculated by using either analytical or simulation methods. The Monte Carlo simulation (MCS) method enables an accurate evaluation of reliability indices. …”
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  12. 12
    An enhanced motion planning method for industrial robots based on the digital twin concept

    An enhanced motion planning method for industrial robots based on the digital twin concept by Rui, Fan

    Published 2025
    “…By integrating an improved Artificial potential field method, A* algorithm, and a synergistic approach combining 3-5-3 polynomial interpolation with particle swarm optimization, we effectively address the challenges of dynamic obstacle avoidance and trajectory optimization. …”
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  13. 13
    A new meta‑heuristic optimization‑based MPPT control technique for green energy harvesting from photovoltaic systems under different atmospheric conditions

    A new meta‑heuristic optimization‑based MPPT control technique for green energy harvesting from photovoltaic systems under different atmospheric conditions by Kishore, Dokala Janandra Krishna, Mohd Rusllim, Mohamed, Sudhakar, Kumarasamy, Peddakapu, kurukuri

    Published 2023
    “…Hence, a new metaheuristic method such as an opposition-based equilibrium optimizer (OBEO) algorithm is used in this work for mitigating the oscillations around GMPP. …”
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  14. 14
    Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System

    Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System by Arab, Ali

    Published 2009
    “…Then, using genetic algorithm-based software which is called SimRunner and has been embedded by ProModel, the scheduling optimization procedure is run to find optimum maintenance schedule. …”
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  15. 15
    Grey number based methodology for non-homogeneous preference elicitation in fuzzy risk analysis management

    Grey number based methodology for non-homogeneous preference elicitation in fuzzy risk analysis management by Abu Bakar, Ahmad Syafadhli, Ku Khalif, Ku Muhammad Naim, Yaakob, Abdul Malek, Gegov, Alexander, Mohamad Amin, Ahmad Zaki

    Published 2019
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  16. 16
    EDITORIAL: INTEGRATION OF HYDROLOGICAL MODELS AND MACHINE LEARNING TECHNIQUES FOR WATER RESOURCES MANAGEMENT

    EDITORIAL: INTEGRATION OF HYDROLOGICAL MODELS AND MACHINE LEARNING TECHNIQUES FOR WATER RESOURCES MANAGEMENT by Ren Jie, Chin, Sai Hin, Lai

    Published 2025
    “…This editorial scope explores the integration of conventional hydrological models with machine learning to improve predictive accuracy, decision-making, and resource optimization. Physics-based models such as SWAT, VIC, and HEC-HMS simulate watershed processes, while hydraulic models like HEC-RAS and MIKE SHE assess flood risks. …”
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  17. 17
    Dynamic investment model for the restructed power market in the presence of wind source

    Dynamic investment model for the restructed power market in the presence of wind source by Esfahani, Mohammad Tolou Askari Sedehi

    Published 2014
    “…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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  18. 18
    Development of optimized maintenance scheduling model for coal-fired power plant boiler

    Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

    Published 2023
    “…Literature revealed that mathematical methods and metaheuristic algorithms are common approaches in solving combinatorial optimization problems with a large search space in a reasonable computational run time. …”
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  19. 19
    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches

    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

    Published 2018
    “…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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  20. 20
    A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties

    A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties by Norhafidzah, Mohd Saad, Muhamad Zahim, Sujod, Mohd Ikhwan, Muhammad Ridzuan, Mohammad Fadhil, Abas, Mohd Shawal, Jadin, Mohd Fadzil, Abdul Kadir

    Published 2024
    “…The Monte Carlo-embedded MVMO-SH was then used to optimise PVDG in the urban RDN. Simulations were run for several scenarios in three load cases based on 288 segments: residential, commercial, and industrial urban loads. …”
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