Search Results - (( developing intensive function algorithm ) OR ( java applications learning algorithm ))
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Comparative analysis of firefly algorithm for solving optimization problems
Published 2017“…Firefly algorithm was developed by Xin-She Yang [1] by taking inspiration from flash light signals which is the source of attraction among fireflies for potential mates. …”
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Book Section -
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Enhancement of Over-Exposed and Under-Exposed Images Using Hybrid Gamma Error Correction Sigmoid Function
Published 2007“…This thesis combines the functions' properties and developed a hybrid algorithm to improve the quality of the poorly captured images by adjusting the contrast and compensating the gamma error. …”
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Thesis -
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An Educational Tool Aimed at Learning Metaheuristics
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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Conference or Workshop Item -
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A video-rate color image segmentation using adaptive and statistical membership function
Published 2010“…Typically, the image segmentation algorithms in video processing system require very high computation power, so it is desirable to develop algorithms for implementation as a real-time system. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
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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The development of semantic meta-database: an ontology based semantic integration of biological databases
Published 2007“…The tool comprises two intelligent algorithms. The first algorithm combines parallel genetic algorithm with the split-and-merge algorithm. …”
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Monograph -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / 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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Jogging activity recognition using k-NN algorithm
Published 2022“…To recognize and classify the level of jogging intensity, k-Nearest Neighbours (k-NN) algorithms will be considered as a machine learning method. …”
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Academic Exercise -
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Development of a scalable video compression algorithm
Published 2012“…The result shows that the managed complexity algorithm based on Lagrangian Multiplier function outperforms the normal encoder. …”
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Proceeding Paper -
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Development Of Machine Learning User Interface For Pump Diagnostics
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Monograph -
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State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm
Published 2023Conference Paper -
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AI powered asthma prediction towards treatment formulation: an android app approach
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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Article -
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Segmentation of Magnetic Resonance Brain Images Using Watershed Algorithm
Published 2004“…The images had a combination of noise and intensity non-uniformity (INU). By making the system semi-automatic, a good segmentation result was obtained under all the conditions (different noise levels and intensity non uniformity). …”
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Bio-signal identification using simple growing RBF-network (OLACA)
Published 2007“…An enhanced online adaptive centre allocation algorithms (or resource allocation network (RAN)) using simple/stochastic back-propagation method with minimal weight update variant are developed for direct-link radial basis function (DRBF) networks. …”
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Conference or Workshop Item -
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Development of sorting system for oil palm in vitro shoots using machine vision approach
Published 2014“…Close results between the performance of the developed sorting algorithm and SVM algorithm demonstrate that it is satisfactory and efficient. …”
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AI powered asthma prediction towards treatment formulation : An android app approach
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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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics
Published 2018“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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Thesis