Search Results - (( java application optimisation algorithm ) OR ( colony estimation method algorithm ))

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  1. 1

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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    Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm by Basri Badyalina, Nurkhairany Amyra Mokhtar, Nur Amalina Mat Jan, Muhammad Fadhil Marsani, Mohamad Faizal Ramli, Muhammad Majid, Fatin Farazh Ya'acob

    Published 2022
    “…It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
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  4. 4

    Artificial Bee Colony-based satellite image contrast and brightness enhancement technique using DWT-SVD by Bhandari, A.K., Soni, V., Kumar, A., Singh, G.K.

    Published 2014
    “…The proposed technique is based on the Artificial Bee Colony (ABC) algorithm using Discrete Wavelet Transform and Singular Value Decomposition (DWT-SVD). …”
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  5. 5

    Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran by Mohammad Reza Pour, Omolbani

    Published 2011
    “…New models based on artificial intelligence models, namely; Ant Colony Optimization (ACO) and Genetic Algorithm (GA) are now being used more frequently to solve optimization problems. …”
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  6. 6

    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

    Published 2015
    “…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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  7. 7

    SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS by YAZID, EDWAR

    Published 2015
    “…The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
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  8. 8

    Fuzzy C means imputation of missing values with ant colony optimization by Mausor, F.H., Jaafar, J., Mohdtaib, S.

    Published 2020
    “…It is a well-known classification method that can provide highest accuracy. It can be benefit from Ant Colony Optimization that can help to select only highly related feature to be process as an estimation for a missing value. …”
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  9. 9

    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter by Yazid, E., Liew, M.S., Parman, S., Kurian, V.J.

    Published 2015
    “…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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  10. 10

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Thus, this thesis precisely developed and evaluated IFS_BACS (Binary Ant Colony System) hybrid method. Further experiments were carried out using the natural domain datasets and comparison were made between IFS and hybrid IFS_BACS methods. …”
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  11. 11

    Multifunctional optimized group method data handling for software effort estimation by Arbain, Siti Hajar

    Published 2022
    “…Group Method of Data Handling (GMDH) algorithms have been widely used for modelling and identifying complex systems and potentially applied in software effort estimation. …”
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  12. 12

    Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices by Ali Abdallah, Ali Emhemed

    Published 2021
    “…The proposed solution is based on the optimization method developed from a combination of the Artificial Bee Colony and Hill Climbing algorithms (ABC-HC) to give the optimal placement and sizing of DG units to be deployed in the system. …”
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  13. 13

    Ant colony optimization (ACO) technique for reactive power planning in power system stability assessment / Mohd Rozely Kalil by Kalil, Mohd Rozely

    Published 2008
    “…ACO is a new cooperative agent’s approach, which is inspired by the observation of the behaviours of real ant colonies on the topics of ant trial formation and foraging method. …”
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  14. 14

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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  15. 15

    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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  16. 16

    Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

    Published 2018
    “…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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    Pid-aco vibration controller with magnetorheological damper for wind turbine tower / Mahmudur Rahman by Mahmudur , Rahman

    Published 2019
    “…At first, appropriate dynamic model is estimated using finite difference method (FDM) and system identification process. …”
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