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  1. 1
    Improving neural networks training using experiment design approach

    Improving neural networks training using experiment design approach by Chong, Wei Kean

    Published 2005
    “…Randomly select the m data set for conventional training algorithm. …”
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  2. 2
    Maximum 2-satisfiability in radial basis function neural network

    Maximum 2-satisfiability in radial basis function neural network by Shehab Abdulhabib Alzaeemi, Saratha Sathasivam, Mohd Shareduwan Mohd Kasihmuddin, Mohd. Asyraf Mansor

    Published 2020
    “…This paper presents a new paradigm in using MAX2SAT by implementing in Radial Basis Function Neural Network (RBFNN). …”
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  3. 3
    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. This is to remedy the problem of using the existing Min-Max (MM) and Decimal Scaling (DS) techniques, which have overflow weakness. …”
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  4. 4
    Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin

    Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin by Alsahag, Ali Mohammed, Mohd Ali, Borhanuddin, Noordin, Nor Kamariah, Mohamad, Hafizal

    Published 2014
    “…In this paper, an efficient bandwidth allocation algorithm for the uplink traffic in mobile WiMAX is proposed. …”
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  5. 5
    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction

    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

    Published 2023
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  6. 6
    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network

    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network by Ismail Abdullah, Kalid Abdlkader Marsal

    Published 2024
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  7. 7
    The development of semantic meta-database: an ontology based semantic integration of biological databases

    The development of semantic meta-database: an ontology based semantic integration of biological databases by Samsudin, Ruhaidah, Deris, Safaai, Othman, Muhammad Razib, Md. Illias, Rosli

    Published 2007
    “…The tool comprises two intelligent algorithms. The first algorithm combines parallel genetic algorithm with the split-and-merge algorithm. …”
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  8. 8
    Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad

    Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad by Mostafa, Modiri Delshad

    Published 2016
    “…Backtracking search algorithm (BSA) as the new evolutionary technique of optimization is used for solving the problems. …”
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  9. 9
    Modern fuzzy min max neural networks for pattern classification

    Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

    Published 2019
    “…To build an efficient classifier model, researchers have introduced hybrid models that combine both fuzzy logic and artificial neural networks. Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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  10. 10
    Effective downlink resource management for wimax networks

    Effective downlink resource management for wimax networks by Shareef, Zayd Ashraf Najeeb

    Published 2018
    “…Our EDRM framework involves three functions: Class-Based Scheduling (CBS) algorithm, Dynamic Bandwidth Allocation (DBA) scheme and Link Session Management (LSM) policy. …”
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  11. 11
    Improved handover decision algorithm using multiple criteria

    Improved handover decision algorithm using multiple criteria by Mohamed Abdullah, Radhwan, Abualkishik, Abedallah Zaid, Alwan, Ali Amer

    Published 2018
    “…The proposed algorithm comprised of three vertical handover decision algorithms, namely: mobile weight, network weight, and equal weight. …”
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  12. 12
    Designing and Developing an Intelligent Congkak

    Designing and Developing an Intelligent Congkak by Muhammad Safwan, Mohd Shahidan

    Published 2011
    “…Therefore the project want to try to rectify this issue by trying to develop an Intelligent Congkak System that also implemented NN and try answer research question such as this: “What is the best Congkak evaluation function for training NN for game playing?” and “Can Min-Max algorithm (MM) be speeded up by using NN as a forward-pruning method?”. …”
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  13. 13
    Performance comparison of differential evolution and particle swarm optimization in constrained optimization

    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.

    Published 2012
    “…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. This paper presents a comparative study for min-max constrained optimization using PSO and DE. …”
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  14. 14
    Reproducing kernel Hilbert space method for cox proportional hazard model

    Reproducing kernel Hilbert space method for cox proportional hazard model by Abdul Manaf, Nur'azah

    Published 2016
    “…Then, we apply the kernel method to the survival data. Finally, we propose an algorithm of minimization of the loss function in the general Cox model. …”
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  15. 15
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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  16. 16
    MBIST implementation and evaluation in FPGA based on low-complexity March algorithms

    MBIST implementation and evaluation in FPGA based on low-complexity March algorithms by Jidin, Aiman Zakwan, Mispan, Mohd Syafiq, Hussin, Razaidi, Weng, Fook Lee

    Published 2024
    “…March algorithms are widely used in Memory Built-In Self-Test (MBIST) on-chip memory testing, providing linear test complexities that reduce the test time and cost. …”
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  17. 17
    Nomadic people optimizer (NPO) for large-scale optimization problems

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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  18. 18
    Development of low power viterbi decoder on complex programmable logic device platform

    Development of low power viterbi decoder on complex programmable logic device platform by Abu, Mohd Azlan

    Published 2018
    “…Consequently, the number of logic gates and the total power consumption of the STTC Viterbi decoder can be reduced by using the new algorithms. The proposed algorithms have been designed and implemented by using MATLAB, Altera Quartus 2 and Altera MAX V CPLD board. …”
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  19. 19
    Simultaneous Computation of Model Order and Parameter Estimation of a Heating System Based on Gravitational Search Algorithm for Autoregressive with Exogenous Inputs

    Simultaneous Computation of Model Order and Parameter Estimation of a Heating System Based on Gravitational Search Algorithm for Autoregressive with Exogenous Inputs by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Sophan Wahyudi, Nawawi, Nor Azlina, Ab. Aziz

    Published 2015
    “…In this paper, an approach termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is basically based on Gravitational Search Algorithm (GSA), is proposed to combine these two parts into a simultaneous solution. …”
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  20. 20
    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming

    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

    Published 2018
    “…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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