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1
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Undergraduates Project Papers -
2
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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Thesis -
3
Facilitating English Language teaching through AI- based drama in Palestine
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Book Chapter -
4
Path Following Using A Learning Neural Network
Published 2004“…The behaviors oflearning rates and updated weights are given special attention in this thesis. To conduct the specified works, the MATLAB programs written by [2] have been extended and modified.…”
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Final Year Project -
5
A review of classification techniques for electromyography signals
Published 2023“…All of the ML classifiers have their own algorithm, special specification, pros and cons based on the available input. …”
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Article -
6
An investigation into influence factor of student programming grade using association rule mining
Published 2010“…This finding can be a guideline to the faculty to plan a teaching and learning program for new registered student.…”
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Article -
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Speed control of separately excited dc motor using artificial intelligent approach
Published 2013“…A neural network controller with learning technique based on back propagation algorithm is developed. …”
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Thesis -
8
Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Published 2025“…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. Materials and Methods: We used hyperspectral reflectance data from healthy and FLS of soybeans. …”
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Article -
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