Search Results - (( interval estimation using algorithm ) OR ( using optimization sensor algorithm ))

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  1. 1

    Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

    Published 2011
    “…In this thesis, we considered two methods via the expectation maximization (EM) algorithm for cure rate estimation based on the BCH model using the two censoring types common to cancer clinical trials; namely, right and interval censoring. …”
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    Thesis
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    Turnbull versus Kaplan-Meier estimators of cure rate estimation using interval censored data by Aljawadi, Bader Ahmad I., Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

    Published 2012
    “…This study deals with the analysis of the cure rate estimation based on the Bounded Cumulative Hazard (BCH) model using interval censored data, given that the exact distribution of the data set is unknown. …”
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  5. 5

    Parametric maximum likelihood estimation of cure fraction using interval-censored data by Aljawadi, Bader Ahmad I., Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma, Al-Omari, Mohamad

    Published 2013
    “…The parametric maximum likelihood estimation method was used for estimation of the cure fraction based on application of the bounded cumulative hazard (BCH) model to interval-censored data. …”
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    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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    Thesis
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    The computation of confidence intervals for the state parameters of power systems by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Fotuhi-Firuzabad, M., Krebs, K.L.

    Published 2016
    “…The research indicates that confidence intervals can yield addition useful information about the estimated parameters. …”
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    The computation of confidence intervals for the state parameters of power systems by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Fotuhi-Firuzabad, M., Krebs, K.L.

    Published 2016
    “…The research indicates that confidence intervals can yield addition useful information about the estimated parameters. …”
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  11. 11

    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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  12. 12

    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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    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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    Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

    Published 2017
    “…The main contribution of the paper is to introduce a dynamic programming algorithm, which defines an optimal policy for solving the visual sensor coverage problem. …”
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    A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network by Gumaida, Bassam, Abubakar, Adamu

    Published 2024
    “…Results: Simulation results perfectly showed that the suggested localization algorithm based on NMM can carry out a better performance than that of other localization algorithms utilizing other op- timization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm (BA). …”
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    A Green Clustering Protocol for Mobile Sensor Network Using Particle Swarm Optimization by ., Nurul Mu’azzah Abdul Latiff NikNoordini, NikAbdMalik Abdul Halim

    Published 2016
    “…One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm.…”
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    Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper by Qadori, Huthiafa Q., Ahmad Zukarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

    Published 2017
    “…The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. …”
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    Mobile robot path optimization algorithm using vector calculus and mapping of 2 dimensional space by Zahari, Ammar, Ismail , Amelia Ritahani, Desia, Recky

    Published 2015
    “…This research explores path integration in mobile robot navigation and path optimization technique using vector calculus. A simulated robot in a simulated environment is used to test the algorithm that is to be developed. …”
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