Search Results - (( mobile location sensor algorithm ) OR ( evolution optimization method algorithm ))

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  1. 1
    A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh

    A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh by Hazem Jihad , Ali Badarneh

    Published 2021
    “…First, the high dependability on multi-attributes (location and time) of packets in random mobile sensors. …”
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  2. 2
    Dynamic area coverage algorithms for static and mobile wireless sensor network environments using voronoi techniques

    Dynamic area coverage algorithms for static and mobile wireless sensor network environments using voronoi techniques by Ceesay, Omar M.

    Published 2011
    “…The proposed Voronoi Tessellation-based Coverage Optimization Algorithms for Static and Mobile Wireless Sensor Networks provides up to 99% coverage at various number of mobile-static sensor node combination and up to 12% reduction in average moving distance. …”
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  3. 3
    Collaborative Location-Based Mobile Game with Error Detection Algorithm

    Collaborative Location-Based Mobile Game with Error Detection Algorithm by Adrus, Mohamad Tazuddin, Wong, Ming Ming, Abang Mohamad Aizuddin, Abang Mohd Mohtar

    Published 2018
    “…From just using buttons, players can now interact with games through a wider spectrum of inputs which includes touch screen, camera, light sensor, accelerometer, compass and GPS. This is driven by the availability of these modules and sensors within mobile devices that are omnipresent nowadays. …”
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  4. 4
    Mobile data gathering algorithms for wireless sensor networks

    Mobile data gathering algorithms for wireless sensor networks by Ghaleb, Mukhtar Mahmoud Yahya

    Published 2014
    “…Minimal Constrained Rendezvous Node (MCRN) algorithm is designed to ensure that the number of pause locations for the mobile element is minimized. …”
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  5. 5
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
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  6. 6
    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields

    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields by Xu, Y., Choi, J., Dass, S., Maiti, T.

    Published 2013
    “…Thus, the prediction algorithm correctly takes into account the uncertainty in hyperparameters in a Bayesian way and is also scalable to be usable for mobile sensor networks with limited resources. …”
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  7. 7
    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields

    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields by Xu, Y., Choi, J., Dass, S., Maiti, T.

    Published 2013
    “…Thus, the prediction algorithm correctly takes into account the uncertainty in hyperparameters in a Bayesian way and is also scalable to be usable for mobile sensor networks with limited resources. …”
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  8. 8
    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields

    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields by Xu, Y., Choi, J., Dass, S., Maiti, T.

    Published 2013
    “…Thus, the prediction algorithm correctly takes into account the uncertainty in hyperparameters in a Bayesian way and is also scalable to be usable for mobile sensor networks with limited resources. …”
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  9. 9
    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields

    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields by Xu, Y., Choi, J., Dass, S., Maiti, T.

    Published 2013
    “…Thus, the prediction algorithm correctly takes into account the uncertainty in hyperparameters in a Bayesian way and is also scalable to be usable for mobile sensor networks with limited resources. …”
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  10. 10
    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields

    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields by Xu, Y., Choi, J., Dass, S., Maiti, T.

    Published 2013
    “…Thus, the prediction algorithm correctly takes into account the uncertainty in hyperparameters in a Bayesian way and is also scalable to be usable for mobile sensor networks with limited resources. …”
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  11. 11
    An energy efficient simultaneous-node repositioning algorithm for mobile sensor networks

    An energy efficient simultaneous-node repositioning algorithm for mobile sensor networks by Khan, M.A., Hasbullah, H., Nazir, B., Khan, I.A.

    Published 2014
    “…A novel algorithm for simultaneous-node repositioning is introduced. …”
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  12. 12
    Autonomous Fire Fighting Mobile Platform

    Autonomous Fire Fighting Mobile Platform by Teh, Nam Khoon, Saman, Abu Bakar Sayuti, Sebastian , Patrick

    Published 2012
    “…The tasks for the AFFMP once it navigates out of the patrolling route include the obstacle avoidance, locating for more precise location of fire source using front flame sensor and extinguish the fire flame. …”
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  13. 13
    Developing stereo vision system for object recognition and positioning of AMAD-R mobile robot

    Developing stereo vision system for object recognition and positioning of AMAD-R mobile robot by Mohd Saifizi, Saidon, Hazry, Desa, Paulraj, Murugesa, Mohd Sofian, M. Rosbi

    Published 2009
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  14. 14
    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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  15. 15
    Simulation and Design of an Intelligent Mobile Robot for Fire Fighting

    Simulation and Design of an Intelligent Mobile Robot for Fire Fighting by Chor, Keong Seng

    Published 2003
    “…Keywords: (Fuzzy logic control, mobile robot, part recognition algorithms)…”
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  16. 16
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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  17. 17
    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy

    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

    Published 2019
    “…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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  18. 18
    Making location-aware computing working accurately in smart spaces

    Making location-aware computing working accurately in smart spaces by Mantoro, Teddy, Ayu, Media Anugerah, Weyn, Maarten

    Published 2011
    “…WiFi, GPS, GSM and Accelerometer. The algorithm is based on opportunistic localization algorithm and fuse different sensor data in order to be able to use the data which is available at the user position and processable in a mobile device.…”
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  19. 19
    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution

    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

    Published 2014
    “…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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  20. 20
    HEAT EXCHANGER NETWORK SYNTHESIS AND OPTIMIZATION BY PINCH ANALYSIS AND DIFFERENTIAL EVOLUTION METHOD

    HEAT EXCHANGER NETWORK SYNTHESIS AND OPTIMIZATION BY PINCH ANALYSIS AND DIFFERENTIAL EVOLUTION METHOD by NGO , THI PHUONG THUY

    Published 2016
    “…This metadology way uses an algorithm which combines Pinch Design Method and Differential Evolution Method. …”
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