Search Results - (( location selection models algorithm ) OR ( panel classification system algorithm ))

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  1. 1

    Identifying Damage Types in Solar Panels Through Surface Image Analysis with Naive Bayes by Wiliani, Ninuk, T.K.A, Rahman, Ramli, Suzaimah

    Published 2024
    “…Identifying and categorizing faults on solar panel surfaces is essential for maintenance, as these defects considerably affect energy output and system efficiency. …”
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    Journal
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    Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

    Published 2024
    “…Further more, an improved non-dominated sorting genetic algorithm with an elite strategy II (IMNSGA-II) has been developed to solve the two bi-objective models, surpassing existing literature’s algorithms such as Pareto Envelope-based Selection Algorithm II (PESA-II) and NSGA-II. …”
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    Thesis
  4. 4

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…The results show that the DRBLTS is more efficient than other estimators discussed in this thesis. The results on the model selection again signify that our proposed robust bootstrap model selection method is more robust than the classical bootstrap model selection.…”
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    Thesis
  5. 5

    Development of integrated models for distribution network design of perishable products by Firoozi, Zahra

    Published 2015
    “…Hence, the inventory-location model is formulated for fixed-lifetime perishable product once by an integrated model and another time by a decoupled model. …”
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    Thesis
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    Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques by Che Soh, Azura, Mohamad Radzi, Nur Fadzilah, Mohamad Yusof, Umi Kalsom, Ishak, Asnor Juraiza, Hassan, Mohd Khair

    Published 2018
    “…Two classification methods, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used in order to investigate the performance of classification accuracy for this E-nose system. …”
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    Article
  8. 8

    Implementation of machine learning algorithms for streamflow prediction of Dokan dam by Sarmad Dashti Latif, Mr.

    Published 2023
    “…Seven statistical indices have been selected to evaluate the performance of the proposed models. …”
    text::Thesis
  9. 9

    Optimal timber transportation planning in tropical hill forest using bees algorithm by Jamaluddin, Jamhuri

    Published 2022
    “…This study proposed a multi-objective linear programming model with Bees algorithm (BA) to find an optimal cost TTP for extraction, forest road, and landing locations. …”
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    Thesis
  10. 10

    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability by Romli, Nurul Atiqah

    Published 2024
    “…The proposed logic embedded into Discrete Hopfield Neural Network and considered the optimization of multi-objective function in the retrieval phase to locate superior final neuron states. A Binary Clonal Selection Algorithm is being proposed to ensure optimal generation of the superior final neuron states. …”
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    Thesis
  11. 11

    Agreement options for negotiation on material location decision of housing development by Utomo, C., Rahmawati, Y.

    Published 2020
    “…The objectives are to find a model for agreement options and coalition, to validate the algorithms of the best fit for material locations and to determine how much the proposed agreement option was achieved. …”
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    Article
  12. 12

    Slice sampler and metropolis hastings approaches for bayesian analysis of extreme data by Rostami, Mohammad

    Published 2016
    “…Here, we have exhaustedly studied all the possible priors for location and scale parameters and come out with a few suggestions for the prior selection of a Gumbel model. …”
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    Thesis
  13. 13

    An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir by Sambo, C.H., Hematpour, H., Danaei, S., Herman, M., Ghosh, D.P., Abass, A., Elraies, K.A.

    Published 2016
    “…The first method is an exhaustive method which uses the concept of design of experiment to search all grids available in the model in order to locate the best possible well locations. …”
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    Conference or Workshop Item
  14. 14

    AUTOMATIC ROUTE FINDER FOR NEW VISITORS by ADNAN, MOHD SHIHAM

    Published 2006
    “…This project proposes a new visitor route model that is based on shortest path algorithms for road networks. …”
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    Final Year Project
  15. 15

    Facility location models development to maximize total service area by Mahmud, Ahmad Rodzi, Indriasari, Vini

    Published 2009
    “…The MSAP is a discrete model where a specified number of facilities that achieve the best objective function value of the model are selected out of a finite set of candidate sites. …”
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    Article
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    Advanced machine learning algorithm to predict the implication of climate change on groundwater level for protecting aquifer from depletion by Ahmed Osman A.I., Latif S.D., Wee Boo K.B., Ahmed A.N., Huang Y.F., El-Shafie A.

    Published 2025
    “…Applying the same 3 different input combinations for the models, the results showed that all the locations, including the GWL time-series data, improved the prediction accuracy significantly in all four models. …”
    Article
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    Using artificial intelligence search in solving the camera placement problem by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P.

    Published 2022
    “…In order to solve the camera placement problem, a crucial fundamental step is modeling the coverage of the cameras in use. Following the coverage modeling, an optimization method needs to be used to locate the optimal poses and/or camera positions. …”
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    Book
  20. 20

    Fault section detection and location on distribution network using analytical voltage sags database by Khalid, A.R., Mokhlis, Hazlie, Li, H.

    Published 2006
    “…By doing this all the possible sections due to the fault can be selected. Finally, the most probable faulty section is identified using probability approach.This paper presents the implemented algorithms and the test of the algorithms on typical distribution networks. …”
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    Conference or Workshop Item