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  1. 1
    Development of a two-level trade credit model with shortage for deteriorating products using hybrid metaheuristic algorithm

    Development of a two-level trade credit model with shortage for deteriorating products using hybrid metaheuristic algorithm by Molamohamadi, Zohreh

    Published 2015
    “…A hybrid metaheuristic algorithm which combines Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm, is then developed to solve the established models. …”
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  2. 2
    Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud

    Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detecti... by Mohd Sayud, Nur Asikin

    Published 2018
    “…Slope variability model is an algorithm that is being used for detecting terrain roughness. …”
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  3. 3
    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain

    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain by Sadrnia, Abdolhossein

    Published 2014
    “…Therefore, various meta-heuristic algorithms have been tried by researchers. In this research, a new Multi-Objective Logistics Network Model for Automotive Closed-Loop Supply Chain (MOACLSC) for recovering ELVs was developed. …”
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  4. 4
    Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi

    Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

    Published 2018
    “…As the mixed integer nonlinear model of the problem was complicated to solve using exact methods, several meta-heuristic algorithms were employed in to optimize the models under investigation. …”
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  5. 5
    Development of a new approach for deterministic supply chain network design

    Development of a new approach for deterministic supply chain network design by Bidhandi, Hadi Mohammadi, Mohd. Yusuff, Rosnah, Megat Ahmad, Megat Mohamad Hamdan, Abu Bakar, Mohd Rizam

    Published 2008
    “…This paper proposes a mixed integer linear programming model and solution algorithm for solving supply chain network design problems in deterministic, multi-commodity, single-period contexts. …”
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  6. 6
    Bayesian inference for the bivariate extreme model

    Bayesian inference for the bivariate extreme model by Mohd Amin, Nor Azrita, Adam, Mohd Bakri

    Published 2016
    “…The bivariate extreme distribution based on logistic dependence function is used to model the extreme observations of two different variables. …”
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  7. 7
    Development of two matheuristics for production-inventory-distribution routing problem / Dicky Lim Teik Kyee

    Development of two matheuristics for production-inventory-distribution routing problem / Dicky Lim Teik Kyee by Dicky Lim , Teik Kyee

    Published 2018
    “…We propose an optimization algorithm designed by the interpolation of metaheuristics and mathematical programming techniques, known as MatHeuristics algorithm, to solve the model. …”
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  8. 8
    A comprehensive model for determining technological innovation level in supply chains using green investment, eco-friendly design and customer collaborations factors

    A comprehensive model for determining technological innovation level in supply chains using green investment, eco-friendly design and customer collaborations factors by Beigizadeh, Razieh, Delgoshaei, Aidin, Ariffin, Mohd Khairol Anuar, Hanjani, Sepehr Esmaeili, Ali, Ahad

    Published 2022
    “…Then, in the last phase (phase 3), the developed model will be used to predict the technological level of supply chains. …”
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  9. 9
    Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout

    Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

    Published 2025
    “…The study employed two MLC frameworks: Problem Transformation methods (Binary Relevance, Classifier Chains, Label Power Set, and Calibrated Label Ranking) and Algorithm Adaptation. …”
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  10. 10
    A salp swarm algorithm to improve power production of wind plant

    A salp swarm algorithm to improve power production of wind plant by Ahmad Zairi, Mohd Zain, Mohd Ashraf, Ahmad

    Published 2019
    “…Currently, the main problem of wind lantpowerproduction is definitely the control system of a wind generator that is not able to cope with the impact of turbulence and thus weakens complete power output.In this papera Salp Swarm Algorithm (SSA) is proposed as a data-drivenmethod to improve the controller variable and thus optimize the complete power production of the wind plant.The SSA is among of the meta-heuristic technique and imitates the salps chain's swarm movement depending on the food placement. …”
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  11. 11
    Model for responsive agriculture hub via e-commerce to sustain food security

    Model for responsive agriculture hub via e-commerce to sustain food security by Wan Ab. Rahman, Wan Nurhayati, Wan Zulkifli, Wan Nurfarah, Zainuri, Nur Nabilah, Anwar, Hanis Amira Khairol

    Published 2024
    “…The model integrates data-driven decision-making, supply chain optimization, and digital marketplaces to enhance the efficiency and resilience of agricultural systems. …”
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  12. 12
    Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting

    Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting by YAXING, WEI, HUZAIFA, HASHIM, Lai, Sai Hin, CHONG, KAI LUN, HUANG, YUK FENG, ALI NAJAH, AHMED, MOHSEN, SHERIF, AHMED, EL-SHAFIE

    Published 2024
    “…Using Bayesian neural networks, we modeled network weights and biases as probability distributions to assess aleatoric and epistemic variability, employing Markov chain Monte Carlo and bootstrap resampling techniques. …”
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  13. 13
    Enhancing obfuscation technique for protecting source code against software reverse engineering

    Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

    Published 2019
    “…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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  14. 14
    An economic order quantity model with completely backordering and nondecreasing demand under two-level trade credit

    An economic order quantity model with completely backordering and nondecreasing demand under two-level trade credit by Molamohamadi, Zohreh, Arshizadeh, Rahman, Napsiah, Ismail, Amir, Azizi

    Published 2014
    “…Two special cases of the proposed model are discussed and the impacts of parameters on the decision variables are finally investigated. …”
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  15. 15
    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
    “…The optimal model based on the parsimony principles was obtained from the hill climbing algorithm with score metrics. …”
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  16. 16
    Optimization of emulsion polymerization of styrene and methyl methacrylate (MMA)

    Optimization of emulsion polymerization of styrene and methyl methacrylate (MMA) by Yok, Loke Kam

    Published 2013
    “…Using gPROMS, the system analyzed the data, created models, developed algorithms, manipulated and plotted based on the functions and data. …”
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  17. 17
    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data

    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

    Published 2018
    “…In addition, BRF ensures that important variables are selected at each subset selection step, thus reducing false signals and eventually improving accuracy of models. …”
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  18. 18
    Detection of Denial of Service Attacks against Domain Name System Using Neural Networks

    Detection of Denial of Service Attacks against Domain Name System Using Neural Networks by Rastegari, Samaneh

    Published 2009
    “…With the prior knowledge of DoS attacks against DNS, we used a network simulator to model DNS traffic with high variability. Therefore, the difficulty of creating different scenarios of attacks in a real environment has been decreased. …”
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  19. 19
    Fault detection and diagnosis using rule-based support system on fatty acid fractionation column

    Fault detection and diagnosis using rule-based support system on fatty acid fractionation column by Yann, H. H., Ali, Mohamad Wijayanuddin, Kamsah, Mohd Zaki

    Published 2003
    “…Identification of causes, consequences and suggested actions for each deviation assisted by Hazard and Operability Study (HAZOP) analysis are generated into rule-based algorithm. Forward chaining strategy is used to interpret the rule-based system. …”
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  20. 20
    Tangible interaction learning model to enhance learning activity processes among children with dyslexia

    Tangible interaction learning model to enhance learning activity processes among children with dyslexia by Jamalai@Jamali, Siti Nurliana

    Published 2024
    “…To find optimum variables, Machine Learning approach needs to be utilized. …”
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