Search Results - (( developing waste maximization algorithm ) OR ( java implementation tree algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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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

“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis by Abujayyab, Sohaib K. M.

“…It is very crucial to have a precise suitability mapping workflow for new landfill sites in the development planning of municipal solid waste management systems. …”
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Controlling Algorithm for Energy-Consumption, Radio Bandwidth and Signal Strength Deploying Single Fitness Function to Solve Coverage Area Problems by Marsal, Kalid Abdlkader, Abdullah, Ismail, Waidah Ismail, Khairi Abdul Rahim

Optimizing strength of directly recycled aluminum chip-based parts through a hybrid RSM-GA-ANN approach in sustainable hot forging by M. Altharan, Yahya, Shamsudin, Shazarel, Lajis, Mohd Amri, Al-Alim, Sami, Yusuf, Nur Kamilah, Mohammed Alduais, Nayef Abdulwahab, M. Ghaleb, Atef, Zhou, Wenbin

“…This work was carried out to study the application of hot press forging (HPF) in recycling AA6061 aluminum chip waste, aiming to optimize operating factors using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Genetic algorithm (GA) strategy to maximize the strength of recycled parts. …”
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Optimizing strength of directly recycled aluminum chip-based parts through a hybrid RSM-GA-ANN approach in sustainable hot forging by M. Altharan, Yahya, Shamsudin, Shazarel, Lajis, Mohd Amri, Al-Alimi, Sami, Yusuf, Nur Kamilah, M. Ghaleb, Atef, Zhou, Wenbin

“…This work was carried out to study the application of hot press forging (HPF) in recycling AA6061 aluminum chip waste, aiming to optimize operating factors using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Genetic algorithm (GA) strategy to maximize the strength of recycled parts. …”
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Optimizing strength of directly recycled aluminum chip-based parts through a hybrid RSM-GA-ANN approach in sustainable hot forging by M. Altharan, Yahya, Shamsudin, Shazarel, Lajis, Mohd Amri, Sami Al-Alimi, Sami Al-Alimi, Yusuf, Nur Kamilah Y, Mohammed Alduais, Nayef Abdulwahab, Atef M. Ghaleb, Atef M. Ghaleb, Wenbin Zhou, Wenbin Zhou

“…This work was carried out to study the application of hot press forging (HPF) in recycling AA6061 aluminum chip waste, aiming to optimize operating factors using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Genetic algorithm (GA) strategy to maximize the strength of recycled parts. …”
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Single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems by Kalid Abdlkader Marsal

Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…The review of optimization studies in the literature contributes to the development of a flowchart of an advanced optimization strategy that serves as a guide for the methodology of the study. …”
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Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin by Husam , N. S. Yasin

“…Hence, it proposes a Q-Learning-based test coverage approach developed in DroidbotX to generate GUI test cases for Android apps. …”
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