Search Results - (( normal optimization _ algorithm ) OR ( using optimization sensor algorithm ))

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  1. 1
    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors

    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

    Published 2025
    “…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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  2. 2
    Modelling of multi-robot system for search and rescue

    Modelling of multi-robot system for search and rescue by Poy, Yi Ler

    Published 2023
    “…In this project, this sensor-based algorithm is known as the Obstacle Avoidance Algorithm. …”
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    Final Year Project / Dissertation / Thesis
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  3. 3
    Dynamic positioning base station for wireless sensor network using particle swarm optimization (PSO)

    Dynamic positioning base station for wireless sensor network using particle swarm optimization (PSO) by Nurul Adilah Abdul Latiff

    Published 2012
    “…Since the optimal selection of base station location in a network belongs to nondeterministic polynomial (NP) hard problem, the use of approximation algorithms such as Particle Swarm Optimization (PSO) are generally more suitable due to its simplicity and outstanding search strength.…”
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  4. 4
    A real-time algorithm of optical tactile sensor for surface characterization / Nurul Fathiah Mohamed Rosli

    A real-time algorithm of optical tactile sensor for surface characterization / Nurul Fathiah Mohamed Rosli by Mohamed Rosli, Nurul Fathiah

    Published 2016
    “…Many advances have been made in terms of sensor technology for sensitivity optimization. Mostly available optical tactile sensors are bulky, inflexible and lack dexterity for applications with limited or space constraint. …”
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  5. 5
    Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks

    Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks by Mujahid Tabassum

    Published 2024
    thesis::doctoral thesis
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  6. 6
    Optimal forwarding routing protocol in ipv6-based wireless sensor network

    Optimal forwarding routing protocol in ipv6-based wireless sensor network by Jamil, Ansar

    Published 2009
    “…Normally, these applications require numerous low cost, low power and low data sensor nodes that communicating over multiple hop to cover a large geographical area. …”
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  7. 7
    Normalized advancement based totally opportunistic routing algorithm with void detection and avoiding mechanism for underwater wireless sensor network

    Normalized advancement based totally opportunistic routing algorithm with void detection and avoiding mechanism for underwater wireless sensor network by Rahman, Ziaur, Hashim, Fazirulhisyam, A. Rasid, Mohd Fadlee, Othman, Mohamed, Alezabi, Kamal Ali Ahmed

    Published 2020
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  8. 8
    Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique

    Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique by Mohd Mawardi, Saari, Mohd Herwan, Sulaiman, Kiwa, Toshihiko

    Published 2023
    “…In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. …”
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  9. 9
    Artificial neural controller synthesis for TORCS

    Artificial neural controller synthesis for TORCS by Shi, Jun Long

    Published 2015
    “…The results showed: (1) DE hybrid FFNN could generate optimal controllers, (2) the proposed fitness function had successfully generated the required car's racing controllers, (3) the proposed minimization algorithm had been successfully minimize the number of RF sensors used, (4) the PDE algorithm could be implemented to generate optimal solutions for car racing controllers, and (5) the combination of components for average car speed and distance between the car and track axis is very important compared to other components. …”
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  10. 10
    A new sinkhole attack detection algorithm for RPL in wireless sensor networks (WSN)

    A new sinkhole attack detection algorithm for RPL in wireless sensor networks (WSN) by Ali, Mohammed Qasim

    Published 2019
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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
    Configuration and analysis of piezoelectric-based in socket sensory system for transfemoral prosthetic Gait detection / Farahiyah Jasni

    Configuration and analysis of piezoelectric-based in socket sensory system for transfemoral prosthetic Gait detection / Farahiyah Jasni by Farahiyah , Jasni

    Published 2018
    “…The accuracy increased by 0.1% when the number of sensors was optimized to 14 sensors. In conclusion, this thesis presents the configuration for the in-socket sensory system for TF prosthesis, and proved that the proposed system is feasible to be used to detect gait phases for level walking. …”
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  13. 13
    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions

    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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  14. 14
    A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles

    A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles by Abdulhasan Al-Jarah, Ali Husam

    Published 2017
    “…Particle Swarm Optimization has been used in the proposed algorithm to minimize the fitness function. …”
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  15. 15
    Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage

    Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Kamarulzaman, Ab Aziz, Nor Hidayati, Abdul Aziz

    Published 2019
    “…It had been successfully used for optimization of many engineering problems. …”
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    Conference or Workshop Item
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  16. 16
    Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network

    Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network by Puteri Azwa, Ahmad

    Published 2014
    “…This study proposed Extended Virtual Force and Cuckoo Search (EVFCS) algorithm with a combination of EVFA and CS algorithm to find an optimal node placement. …”
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  17. 17
    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm

    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

    Published 2020
    “…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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  18. 18
    Global optimization method for continuous - Time sensor scheduling

    Global optimization method for continuous - Time sensor scheduling by Woon, Siew Fang, Rehbock, Volker, Loxton, Ryan C.

    Published 2010
    “…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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  19. 19
    Framework for pedestrian walking behaviour recognition to minimize road accident

    Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

    Published 2021
    “…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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  20. 20
    Framework for pedestrian walking behaviour recognition to minimize road accident

    Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

    Published 2021
    “…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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