Search Results - (( a distribution factor algorithm ) OR ( _ valuation ((bees algorithm) OR (based algorithm)) ))

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  1. 1

    Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

    Published 2021
    “…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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    The Performance of Chlorophyll-a Distribution Estimation by Using Ratio Algorithm on Landsat-8 in Sungai Merbok Estuary / Jesse Vince Rabing ... [et al.] by Rabing, Jesse Vince, Abd.Aziz, Khairul Naim, Kamaruddin, Sharir Aizat, Roslani, Muhammad Akmal, Tajam, Jamil, Ahmad, Aziani, Nazri, Rosnani, Zainol, Zamzila Erdawati, Ramli, Rohayu, Shaari, Mohd Idrus

    Published 2022
    “…This study explores the applicability of ratio algorithms for estimation of the chl- a concentration at Sungai Merbok by assessing chl-a distribution pattern built by the algorithms and evaluating each algorithm for their errors compared to in-situ data. …”
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  4. 4

    Efficient signaling schedule for centralized and distributed scheduling algorithms for wimax multi-hop relay networks by Saqer, Ahmad Sabri Mousa

    Published 2012
    “…On the other hand, the proposed distributed scheduling algorithm (MR-DSA) was evaluated by comparing its performance against performances of Greedy and the factor-graph-based low-complexity distributed scheduling algorithm (FGDS) algorithms in terms of delay, throughput, and overhead. …”
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  5. 5

    Investigation of relaxation factor in landweber iterative algorithm for electrical capacitance tomography by Tian, Wenbin, Ramli, Mimi Faisyalini, Yang, Wuqiang, Sun, Jiangtao

    Published 2020
    “…It is crucial to select a suitable relaxation factor in iterative image reconstruction algorithms (e.g. …”
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  6. 6

    Comparison between specifications of linear regression and spatial-temporal autoregressive models in mass appraisal valuation for single storey residential property by Jahanshiri, Ebrahim

    Published 2013
    “…Property valuation is an area of interest for property owners, real estate agents, government bodies and researchers. …”
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  7. 7

    Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat by Yuliant, Sibaroni, Sri Suryani, Prasetiyowati, Iqbal Bahari, Sudrajat

    Published 2020
    “…Determination of the best factor is carried out in a genetic algorithm by combining several parameters of the crossover probability (Pc) and mutation probability (Pm). …”
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    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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  10. 10

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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  11. 11

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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  12. 12

    Stochastic fractal search algorithm for reconfiguration of distribution networks with distributed generations by Tran, T.T., Truong, K.H., Vo, D.N.

    Published 2020
    “…The SFS is a meta-heuristic algorithm inspired by the fractal theory for solving optimization problems. …”
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  13. 13

    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

    Published 2022
    “…There is a need to achieve optimality in allocating and sizing of DG in the distribution system network. …”
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    An enhanced metaheuristic approach to solve quadratic assignment problem using hybrid technique by Hameed, Asaad Shakir

    Published 2021
    “…The valuate of performance HDDETS algorithm comparison to existing hybrid-based algorithms, namely: Biogeography-Based Optimization Tabu Search (BBOTS), Whale Algorithm with Tabu Search (WAITS), Hybrid Ant System (HAS), Lexisearch and Genetic Algorithms (LSGA), and Golden Ball Simulated Annealing (GBSA) algorithms. …”
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    Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal by Zainal, Mohamad Izwan

    Published 2022
    “…Furthermore, the isolation line is tested on different section and load factor to recognize the improvement of optimal distribution network performance. …”
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    Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm by Mohamad Zunnurain Fauzi

    Published 2023
    “…The DG units have a few advantages, for example reduced distribution losses, improve the voltage profile, reduced capacity costs and the most important thing being environmentally friendly. …”
    text::Final Year Project
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    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…The DG units have to be allocated with optimal sizes in the network to reach maximum efficacy. A new meta-heuristic optimization technique called the Slime Mould Algorithm (SMA) approach has a high convergence rate or a few iterations and superior optimization indices analyzed against other algorithms. …”
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