Search Results - (( java application optimisation algorithm ) OR ( using integration selection algorithm ))

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  1. 1

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

    Published 2015
    “…Secondly, an expert system using Java programming technology with two tiers of search engine was developed to perform a fast selection of candidate materials in huge volume. …”
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    Thesis
  2. 2

    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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    Article
  3. 3

    VHDL modeling of optimum measurement selection by using genetic algorithm by Ullah, Mohammad Habib, Hasan, Muhammad Asfarul, Uddin, Md. Jasim, Priantoro, Akhmad Unggul

    Published 2009
    “…The purpose of this research is to come up with hardware based Genetic Algorithm that is used in Optimum Measurement Selection.…”
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    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

    Published 2004
    “…ECQ Routing Algorithm is integrates the Variable of Decay Constant and Update All Q Value approaches for updating the C values of non-selected Q values. …”
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  7. 7

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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  8. 8

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The combined influence of the genetic algorithm and correlation analysis are used in this technique. …”
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  9. 9

    SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

    Published 2016
    “…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. …”
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  10. 10

    Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique by Muhammad Hanafi, Yusop

    Published 2018
    “…The current research presents the implementation of an integrated kurtosisbased algorithm for a z-filter technique (Ikaz) to kurtosis ratio (Ikaz-kurtosis), for this allows automatic selection of the IMF that should be used. …”
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  11. 11

    An integrated algorithm of analytical network process with case-based reasoning to support the selection of an ideal football team formation and players by Mohammad Zukuwwan, Zainol Abidin

    Published 2021
    “…However, there are very few algorithms or decision engines available that could actually be used by decision-makers to aid in the process of forming a football team. …”
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  12. 12

    Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF) by Mazlan, Nurul Hidayah

    Published 2019
    “…The related best features in the sample are selected using weight and priority ranking process using K-means. …”
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  13. 13

    Implementation of local proprietary symmetric and asymmetric algorithm as secure plug-in on microsoft outlook / Mohd Izhar Jaafar by Jaafar, Mohd Izhar

    Published 2012
    “…Apart from symmetric algorithm, Public Key Infrastructure technologies that one of the asymmetric algorithm have been select as a part of new integration. …”
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  14. 14

    Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925) by Kamarudin, Nur Azulia

    Published 2021
    “…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
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    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Support Vector Machine (SVM) is a present day classification approach originated from statistical approaches.Two main problems that influence the performance of SVM are selecting feature subset and SVM model selection. In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…In conclusion, SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics can be used as models selection algorithms. Additionally, both algorithms are suitable in improving performance of automated models selection procedures. …”
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    Melanoma skin cancer recognition using negative selection algorithm / Muhammad Rushamir Hakimi Ruslan by Ruslan, Muhammad Rushamir Hakimi

    Published 2017
    “…This study proposed and focused on the development of a prototype that uses the Negative Selection Algorithm to classify the input image whether it is belongs to melanoma skin cancer or benign mole. …”
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    Proportional-integral control optimization using imperialist competitive algorithm by Soheilirad, Mohammadsoroush

    Published 2012
    “…In this dissertation, an attempt has been made to design and implement the PID Controllers by employing the Imperialist Competitive Algorithm (ICA) technique as well as the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm, for a selected plant. …”
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