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  1. 1
    Study and Implementation of Data Mining in Urban Gardening

    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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  2. 2
    An enhanced feed-forward neural networks and a rule-based algorithm for predictive modelling of students' academic performance

    An enhanced feed-forward neural networks and a rule-based algorithm for predictive modelling of students' academic performance by Raheem, Ajiboye Adeleke

    Published 2016
    “…Findings from the comparison show that, the proposed RBA explores students‟ data much better. It can also serve as an alternative algorithm to the use of machine learning techniques in the exploration of students‟ data for prediction purposes.…”
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  3. 3
    A Standard Deviation Selection in Evolutionary Algorithm for Grouper Fish Feed Formulation

    A Standard Deviation Selection in Evolutionary Algorithm for Grouper Fish Feed Formulation by Soong, Cai Juan, Razamin, Ramli, Rosshairy, Abdul Rahman

    Published 2016
    “…In order to farm grouper fish, there is a need to have prior knowledge of the proper nutrients needed because there is no exact data available. Therefore, in this study, primary data and secondary data are collected even though there is a limitation of related papers and 30 samples are investigated by using standard deviation selection in Evolutionary algorithm. …”
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  4. 4
    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
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  5. 5
    Web-based expert system for material selection of natural fiber- reinforced polymer composites

    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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  6. 6
    A standard deviation selection in evolutionary algorithm for grouper fish feed formulation

    A standard deviation selection in evolutionary algorithm for grouper fish feed formulation by Soong, Cai Juan, Ramli, Razamin, Abdul Rahman, Rosshairy

    Published 2016
    “…Malaysia is one of the major producer countries for fishery production due to its location in the equatorial environment.Grouper fish is one of the potential markets in contributing to the income of the country due to its desirable taste, high demand and high price.However, the demand of grouper fish is still insufficient from the wild catch.Therefore, there is a need to farm grouper fish to cater to the market demand.In order to farm grouper fish, there is a need to have prior knowledge of the proper nutrients needed because there is no exact data available.Therefore, in this study, primary data and secondary data are collected even though there is a limitation of related papers and 30 samples are investigated by using standard deviation selection in Evolutionary algorithm.Thus, this study would unlock frontiers for an extensive research in respect of grouper fish feed formulation.Results shown that the fitness of standard deviation selection in evolutionary algorithm is applicable.The feasible and low fitness, quick solution can be obtained. …”
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  7. 7
    Prediction of cascading collapse occurrence due to the effect of hidden failure protection system using different training algorithms feed-forward neural network / N. H. Idris ...[et al.]

    Prediction of cascading collapse occurrence due to the effect of hidden failure protection system using different training algorithms feed-forward neural network / N. H. Idris ...[... by Idris, N. H., Salim, N. A., Othman, M. M., Yasin, Z. M.

    Published 2017
    “…The historical data obtained from NERC report is analyzed and being used in ANN for prediction purposed. …”
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  8. 8
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The most widely used source of such data is the Machining Data Handbook (MDH) published by Metcut Research Association, (1980). …”
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  9. 9
    The Identification of hunger behaviour of lates calcarifer using k-nearest neighbour

    The Identification of hunger behaviour of lates calcarifer using k-nearest neighbour by Zahari, Taha, Mohd Azraai, M. Razman, N. F., Adnan

    Published 2018
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  10. 10
    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer

    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

    Published 2023
    “…The AADS algorithm uses evolving methods which are evolving autonomous data partitioning (eADP) and non-weighted frequency equations. …”
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  11. 11
    Energy cost optimization in high speed hard turning using simulated annealing algorithm

    Energy cost optimization in high speed hard turning using simulated annealing algorithm by Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Hassan, Muhammad Hasibul, Shaffiar, Norhashimah

    Published 2015
    “…Then, the Simulated Annealing Algorithm (SAA) has been used to optimize the cutting parameters. …”
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  12. 12
    Using an Enhanced Feed-Forward BP Network for Predictive Model Building From Students’ Data

    Using an Enhanced Feed-Forward BP Network for Predictive Model Building From Students’ Data by Ajiboye, Adeleke Raheem, Ruzaini, Abdullah Arshah, Qin, Hongwu

    Published 2015
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  13. 13
    The identification of hunger behaviour of lates calcarifer using k-nearest neighbour

    The identification of hunger behaviour of lates calcarifer using k-nearest neighbour by Taha, Zahari, Mohd Razman, Mohd Azraai, A. Adnan, Fatihah, Abdul Majeed, Anwar P.P., Musa, Rabiu Muazu, Abdul Ghani, Ahmad Shahrizan, Sallehudin, Muhammad Firdaus, Mukai, Yukinori

    Published 2018
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  14. 14
    Extraction of Inherent Frequency Components of Multiway EEG Data Using Two-Stage Neural Canonical Correlation Analysis

    Extraction of Inherent Frequency Components of Multiway EEG Data Using Two-Stage Neural Canonical Correlation Analysis by W Omar Ali Saifuddin, Wan Ismail, A. N. M. Enamul, Kabir

    Published 2014
    “…An algorithm is developed using two-stage cascaded architecture of canonical correlation analysis with neural network named multiway neural canonical correlation analysis (MNCCA) to address three major challenges for extracting frequency components from EEG data, such as: (a) It processes multiway data which are feed sequentially into neural network, rather than feeding whole data at a time, (b) It uses the conventional personal computer instead of special computer built for such application, (c) It spends very short time for a moderate data set consisting of several ways (time, trials and channels). …”
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  15. 15
    Training functional link neural network with ant lion optimizer

    Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2020
    “…Since FLNN uses Backpropagation algorithm as the standard learning algorithm, the method however prone to get trapped in local minima which affect its performance. …”
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  16. 16
    PREDICTING THE PRICE OF COTTON USING RNN AND LSTM

    PREDICTING THE PRICE OF COTTON USING RNN AND LSTM by MOHAMAD, AHMAD LUKMAN

    Published 2020
    “…The data will then be separated into training set and testing set and will be feed to the machine learning algorithm to find the pattern and try to do prediction. …”
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  17. 17
    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage

    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…The objective of this paper is to introduce a combination of advantages of different algorithm scheme into one learning algorithm. For this purpose, three models is developed, first using recursive least square algorithm (RLS), second using recursive instrument variable (RIV) algorithm and lastly using combination of this two algorithms. …”
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  18. 18
    Ensemble dual recursive learning algorithms for identifying flow with leakage

    Ensemble dual recursive learning algorithms for identifying flow with leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…The objective of this paper is to introduce a combination of advantages of different algorithm scheme into one learning algorithm. For this purpose, three models is developed, first using recursive least square algorithm (RLS), second using recursive instrument variable (RIV) algorithm and lastly using combination of this two algorithm. …”
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  19. 19
    Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset

    Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset by Amirruddin, A., Aziz, I.A., Hasan, M.H.

    Published 2020
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  20. 20
    Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm

    Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm by Alam, Md. Shah, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah, Konneh, Mohamed

    Published 2010
    “…Machining was performed on a five-axis NC milling machine with a high speed attachment, using spindle speed, feed rate, and depth of cut as machining variables. …”
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