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  1. 1
    Multi-Swarm bat algorithm

    Multi-Swarm bat algorithm by Taha A.M., Chen S.-D., Mustapha A.

    Published 2023
    “…In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. …”
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  2. 2
    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff

    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2017
    “…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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  3. 3
    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
    “…In this project, the same centralized relocating algorithm from the previous research has been used where 15 mobile sensors deployed randomly in a field of 100 meter by 100 meter where these sensors has been deployed one time in a field that obstacles does not exist (case 1) and another time in a field that obstacles existence has been taken into account (case 2), in which these obstacles has been pre-defined positions, where these two cases applied into two different algorithms, which are the original algorithm of a previous research and the modified algorithm of this thesis. …”
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  4. 4
    Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory

    Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory by Ng, Peng Hong

    Published 2015
    “…The effects of sensor faults in terms of sensor fault scenarios are investigated in the case studies. …”
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  5. 5
    Performance of various forecasting algorithms to reduce the number of transmitted packets by sensor node in wireless sensor networks

    Performance of various forecasting algorithms to reduce the number of transmitted packets by sensor node in wireless sensor networks by Husni, Muhammed Ihsan

    Published 2018
    “…The simulation experiments are done using MATLAB software for a variety of algorithms. …”
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  6. 6
    Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization

    Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization by Shaikh, Muhammad Suhail, Wang, Chang, Xie, Senlin, Zheng, Gengzhong, Dong, Xiaoqing, Qiu, Shuwei, Mohd Ashraf, Ahmad, Raj, Saurav

    Published 2025
    “…Similarly, in Case 3, with 40 sensor nodes, the coverage rate is 91.6875%, and in Case 4, with 50 sensor nodes, it is 99.4940%. …”
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  7. 7
    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system

    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2018
    “…One of the important issues for sensors is the accuracy of distance measurement. This thesis explains the development of new algorithm for distance measurement using stereo vision sensor. …”
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  8. 8
    LCSS-Based Algorithm for Computing Multivariate Data Set Similarity: A Case Study of Real-Time WSN Data

    LCSS-Based Algorithm for Computing Multivariate Data Set Similarity: A Case Study of Real-Time WSN Data by Khan, Rahim, Ali, Ihsan, Altowaijri, Saleh, Zakarya, Muhammad, Rahman, Atiq Ur, Ahmedy, Ismail, Khan, Anwar, Gani, Abdullah

    Published 2019
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  9. 9
    Collision avoidance algorithm design for UAV base on parametric theorem and circle overlapping method / Nur Fadzilah Mohamad Radzi

    Collision avoidance algorithm design for UAV base on parametric theorem and circle overlapping method / Nur Fadzilah Mohamad Radzi by Nur Fadzilah, Mohamad Radzi

    Published 2013
    “…Finally, the collision avoidance algorithm is verified through MATLAB software. Various cases are tested to demonstrate the robustness of both collision detection and avoidance algorithms.…”
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  10. 10
    Faulty sensor detection using data correlation of multivariant sensor reading in smart agriculture with IOT

    Faulty sensor detection using data correlation of multivariant sensor reading in smart agriculture with IOT by Malik, Ahmed Dhahir

    Published 2019
    “…This method will be applied to the smart agriculture which uses multi-variate sensors such as moisture sensor, temperature sensor and water sensor in IoT. …”
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  11. 11
    Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study

    Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

    Published 2019
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  12. 12
    On Clustering Algorithm Of Coverage Area Problems In Wireless Sensor Networks

    On Clustering Algorithm Of Coverage Area Problems In Wireless Sensor Networks by Ismail Abdullah, Kalid Abdlkader Marsal

    Published 2024
    “…In the case study, many algorithms have been proposed in the literature, in order to find the maximum number of disjoint or non-disjoint sets of sensor cover sets, we can see where one set can be active at any one time. …”
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  13. 13
    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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  14. 14
    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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  15. 15
    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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  16. 16
    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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  17. 17
    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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  18. 18
    Minimising coverage holes for prediction-based mobile object target tracking in wireless sensor networks

    Minimising coverage holes for prediction-based mobile object target tracking in wireless sensor networks by Ali, Khalid Abdullahi

    Published 2017
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  19. 19
    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
    “…Therefore, all sensor nodes use extra power to transmit its data to this far base station and result in higher energy consumption. …”
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  20. 20
    A wheelchair sitting posture detection system using pressure sensors

    A wheelchair sitting posture detection system using pressure sensors by Mohamad Yusoff, Muhammad Annuar Alhadi, Azmi, Nur Liyana, Nordin, Nor Hidayati Diyana

    Published 2024
    “…All the classification algorithms were evaluated by using the k-fold cross validation method. …”
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