Search Results - (( practical application optimisation algorithm ) OR ( java adaptation optimization algorithm ))

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    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The works related to swarm intelligence algorithms include the development of the algorithm itself, its modification and improvisation as well as its application in solving global optimisation problems. …”
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    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

    Published 2022
    “…Practically, this FAHA has great potential applications for the optimal allocation and sizing of DG in the radial distribution network.…”
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    Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail by Ismail, Nor Laili

    Published 2024
    “…In this study, a new optimisation algorithm termed Hybrid Evolutionary-Barnacles Mating Optimisation (HEBMO) was initially formulated to solve optimisation problems. …”
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    A Hybrid Metaheuristic Technique Based on Grey Wolf Optimisation, Symbiotic Organism Search, and Ant Colony Optimisation for Solving Multi-Objective Vehicle Routing Problems by Ary, Maxsi

    Published 2025
    “…The findings also highlight the applicability of HMGSA in real-world courier services, contributing theoretically and practically to logistics optimisation. …”
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    Optimisation of the squeeze forming process by Ahmad, Rosli

    Published 2006
    “…The Finite Element Method has been used to simulate the process and a Genetic Algorithm was used as an optimisation tool. The thermal optimisation has been applied to the squeeze f0Il11ing process to achieve near simultaneous solidification in the cast part. …”
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    A competitive co-evolutionary approach for the nurse scheduling problem by Mohamad Nazri, Maizatul Farhana, Mohd Yusoh, Zeratul Izzah, Basiron, Halizah, Daud, Azlina

    Published 2026
    “…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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    An improved fair nurse scheduling optimisation using particle swarm intelligent technique by Ramli, Mohamad Raziff

    Published 2015
    “…The suggested approach provides better solution not only with respect to efficiency but also the quality of the nurse scheduling to the hospital and the nurse themselves. Particle Swarm Optimisation (PSO) has many successful applications in continuous optimisation problems, thus, the capability of PSO is used to provide a high performance predictive nurse schedule. …”
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    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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    Design issues and challenges of an FPGA-based orthogonal matching pursuit implementation for compressive sensing reconstruction by Mohd Nadzri,, Muhammad Muzakkir, Ahmad, Afandi, Tukiran, Zarina

    Published 2020
    “…To date, the implementation of practical applications of CS in hardware platforms, especially in real-time applications, still faces challenging issues due to the high computational complexity of its algorithms, hence leading to high power-consuming processes. …”
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    Optimisation and performance evaluation of response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) in the prediction o... by Chong, D.J.S., Chan, Y.J., Arumugasamy, S.K., Yazdi, S.K., Lim, J.W.

    Published 2023
    “…In recent years, machine learning (ML) techniques have been developed to predict the performance of anaerobic digestion (AD) processes including methane potential and reactor stability. However, their practical applications to industrial-scale palm oil mill effluent (POME) treatment plant are limited. …”
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