Search Results - (( parameter simulation based algorithm ) OR ( interval optimization based algorithm ))

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  1. 1
    Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm

    Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2018
    “…In order to overcome this limitation in an ELM-based IT2FLS, artificial bee colony optimization algorithm is utilized to obtain its antecedent parts parameters. …”
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  2. 2
    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS

    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…In this paper, heuristic optimization approaches such as genetic algorithm and artificial bee colony are used to optimize the parameters of the antecedent part of interval type-2 fuzzy logic systems. …”
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  3. 3
    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks

    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks by Mubarak, Mohammed Awadh Ahmed Ben

    Published 2013
    “…It reduces the number of handovers by 29.7% and 26.9%, respectively, compared to the conventional RSSI based handover algorithm and the previous worked, mobility improved handover (MIHO) algorithm. …”
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  4. 4
    Adaptive manet OLSR routing protocol for optimal route selection in high dynamic network

    Adaptive manet OLSR routing protocol for optimal route selection in high dynamic network by Al-Kharasani, Nori Mohammed Abdulkarem

    Published 2020
    “…For these reasons, optimizing routing configuration parameters, the cluster-based Quality of Service (QoS) and cross-layer parameters are an effective technique and widely accepted to improve routing performance. …”
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  5. 5
    Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun

    Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

    Published 2021
    “…As for the optimization process, the reservoir operation rule was derived using a meta-heuristic algorithm at the monthly interval. …”
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  6. 6
    A DC/DC buck-boost converter-inverter-dc motor control based on model-free PID controller tuning by adaptive safe experimentation dynamics algorithm

    A DC/DC buck-boost converter-inverter-dc motor control based on model-free PID controller tuning by adaptive safe experimentation dynamics algorithm by Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Zaidi, Mohd Tumari

    Published 2022
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  7. 7
    Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks

    Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks by Iranpanah, Havzhin

    Published 2017
    “…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
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  8. 8
    A Data-driven Sigmoid-based Secretion Rate of Neuroendocrine-PID Control for TRMS System

    A Data-driven Sigmoid-based Secretion Rate of Neuroendocrine-PID Control for TRMS System by Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Haszuraidah, Ishak

    Published 2021
    “…This paper investigated the implementation of datadriven sigmoid-based secretion rate of neuroendocrine-PID (SbSR-NEPID) within a twin-rotor MIMO system (TRMS), based on the adaptive safe experimentation dynamics (ASED) algorithm. …”
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  9. 9
    Data-driven neuroendocrine-pid tuning based on safe experimentation dynamics for control of TITO coupled tank system with stochastic input delay

    Data-driven neuroendocrine-pid tuning based on safe experimentation dynamics for control of TITO coupled tank system with stochastic input delay by Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Raja Mohd Taufika, Raja Ismail

    Published 2019
    “…This paper addresses a data-driven neuroendocrine-PID tuning for the control of a two-input-two-output (TITO) coupled tank system with sto-chastic input time delay based on safe experimentation dynamics (SED). The SED algorithm is an optimization method used as data-driven tools to find the optimal control parameters by using the input-output (I/O) data measurement in an actual system. …”
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  10. 10
    A data-driven sigmoid-based secretion rate of neuroendocrine- pidcontrol for TRMS system

    A data-driven sigmoid-based secretion rate of neuroendocrine- pidcontrol for TRMS system by Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Haszuraidah, Ishak

    Published 2021
    “…This paper investigated the implementation of data-driven sigmoid-based secretion rate of neuroendocrine-PID (SbSR-NEPID) within a twin-rotor MIMO system (TRMS), based on the adaptive safe experimentation dynamics (ASED) algorithm. …”
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  11. 11
    QoS BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK

    QoS BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK by NAZIR, BABAR

    Published 2012
    “…Clustering within normal sensor nodes is done by optimizing the network/coverage lifetime through a cluster-head-selection algorithm and a sleep/wake scheduling algorithm. …”
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  12. 12
    Structural health monitoring using adaptive wavelet functions / Seyed Hossein Mahdavi

    Structural health monitoring using adaptive wavelet functions / Seyed Hossein Mahdavi by Seyed Hossein, Mahdavi

    Published 2016
    “…For this purpose, a wavelet-based GAs strategy is improved by using free-scaled adaptive wavelets to optimally identify unknown structural parameters. …”
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  13. 13
    Vehicular traffic noise prediction and propagation modelling using artificial neural network

    Vehicular traffic noise prediction and propagation modelling using artificial neural network by Ahmed, Ahmed Abdulkareem

    Published 2018
    “…The neural network and its hyperparameters were optimized through a systematic optimization procedure based on a grid search approach. …”
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  14. 14
    Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment

    Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment by M. F., Masrom, N. M. A., Ghani, M. O., Tokhi

    Published 2021
    “…It is shown that the particle swarm optimization-based control mechanism performs better than the spiral dynamic algorithm-based control in terms of system stability, disturbance rejection and reduce noise. …”
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  15. 15
    Neural network approach for global solar irradiance prediction at extremely short-time-intervals using particle swarm optimization algorithm

    Neural network approach for global solar irradiance prediction at extremely short-time-intervals using particle swarm optimization algorithm by Aljanad A., Tan N.M.L., Agelidis V.G., Shareef H.

    Published 2023
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  16. 16
    Lifting and stabilizing of two-wheeled wheelchair system using interval type-2 fuzzy logic control based spiral dynamic algorithm

    Lifting and stabilizing of two-wheeled wheelchair system using interval type-2 fuzzy logic control based spiral dynamic algorithm by N. A. A., Razali, N. M. A., Ghani, B. S., Bari

    Published 2021
    “…The current study emphasizes on improving an interval type-2 fuzzy logic control (IT2FLC) system through the use of spiral dynamics algorithm (SDA) optimization in stabilizing a transformational two-wheeled wheelchair. …”
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  17. 17
    Application of induced preorderings in score function-based method for solving decision-making with interval-valued fuzzy soft information

    Application of induced preorderings in score function-based method for solving decision-making with interval-valued fuzzy soft information by Ali, Mabruka, Kilicman, Adem, Khameneh, Azadeh Zahedi

    Published 2021
    “…Currently, there are three interval-valued fuzzy soft set-based decision-making algorithms in the literature. …”
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  18. 18
    Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm

    Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2018
    “…The results for the Wilson flood showed that the proposed model could reduce the Sum of Squared Deviations (SSD) value by 89%, 51%, 93%, 69%, and 88%, compared to the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Pattern Search (PS) algorithm, Harmony Search (HS) algorithm, and Honey Bee Mating Optimization (HBMO), respectively. …”
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  19. 19
    Hybrid genetic manta ray foraging optimization and its application to interval type 2 fuzzy logic control of an inverted pendulum system

    Hybrid genetic manta ray foraging optimization and its application to interval type 2 fuzzy logic control of an inverted pendulum system by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir, Normaniha, Abd Ghani, Shuhairie, Mohammad, Mohd Falfazli, Mat Jusof, Nurul Amira, Mhd Rizal

    Published 2020
    “…MRFO is a recent proposed algorithm which based on the behaviour of manta rays. …”
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  20. 20
    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre

    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2018
    “…The purpose of this study is to observe the reliability of genetic algorithm in our previously simulated network optimization in a data centre. …”
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