Search Results - (( variable implementation some algorithm ) OR ( java application learning algorithm ))

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    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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    Numerical algorithm of block method for general second order ODEs using variable step size by Nazreen Waeleh, Zanariah Abdul Majid

    Published 2017
    “…Five numerical examples are considered and some comparisons are made with the existing methods for demonstrating the validity and reliability of the proposed algorithm.…”
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    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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    Security analysis of blowfish algorithm by Alabaichi, Ashwak Mahmood, Ahmad, Faudziah, Mahmod, Ramlan

    Published 2013
    “…C++ is used in the implementation of the blowfish algorithm; MATLAB programming (Mathworks, R., 2012a) is used in the implementation of avalanche effect and correlation coefficient.…”
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    Numerical algorithm of block method for general second order ODEs using variable step size by Waeleh, Nazreen, Abdul Majid, Zanariah

    Published 2017
    “…Five numerical examples are considered and some comparisons are made with the existing methods for demonstrating the validity and reliability of the proposed algorithm.…”
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    Article
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    Security analysis of blowfish algorithm by Al-Abiachi, Ashwak M., Ahmad, Faudziah, Mahmod, Ramlan

    Published 2013
    “…The results obtained from the analysis of correlation coefficient showed that Blowfish algorithm gives a good nonlinear relation between plaintext and ciphertext while the results of avalanche effect indicate that the algorithm presents good avalanche effect from the second round.C++ is used in the implementation of the blowfish algorithm; MATLAB programming (Mathworks, R., 2012a) is used in the implementation of avalanche effect and correlation coefficient.…”
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    AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

    Published 2022
    “…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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    AI powered asthma prediction towards treatment formulation : An android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, Sarker, Md. Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md.

    Published 2022
    “…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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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
    “…Therefore, in this paper, we enhance the GMDH model by implementing the ABC algorithm to optimize the parameter of partial description GMDH model with some transfer functions, namely polynomial, radial basis, sigmoid and hyperbolic tangent function. …”
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    A hybrid model of system dynamics and genetic algorithm to increase crude palm oil production in Malaysia by Mohd Zabid, M. Faeid

    Published 2018
    “…However, these non-hybridized methods have some shortcomings and can be improved by hybridization method. …”
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    Comparing means of two non-homogeneous normal populations by Abd Rahman, Mohd Nawi

    Published 1986
    “…The statistic is a funtion of the three M.L. estimates. A simple algorithm which can be implemented on a microcomputer is proposed for calculating the required values. …”
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    Dynamic Feedback Flow Control Algorithms for Unicast and Multicast Available Bit Rate Service in Asynchronous Transfer Mode Networks by Abdelrahman, Ali Mohamed

    Published 2000
    “…Some of these algorithms do not measure the actual ABR traffic load which leads to either overestimates or underestimates of the bandwidth allocation. …”
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    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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    A case study on quality of sleep and health using Bayesian networks by Hong , Choon Ong, Chiew , Seng Lee, Chye , Ching Sia

    Published 2012
    “…The network scores computation is implemented to estimate the fitting of the resulting network of each structural learning algorithm in order to choose the best-fitted network. …”
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