Search Results - (( developing waste generation algorithm ) OR ( java application tree algorithm ))
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Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia
Published 2025“…It is crucial for developing countries such as Malaysia to be able to accurately predict future municipal solid waste generations in order to achieve high-quality waste management. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…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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Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill
Published 2019“…Leachate generation is related to several factors, including meteorological data, waste generation rates, and landfill design conditions. …”
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Faculty timetabling using genetic algorithm
Published 2011“…Faculty Timetabling using Genetic Algorithm (FTGA) is an application that generate optimum timetable for faculty.The target user of this application is faculty staff who responsible in generate timetable.The problem statement of the project is many clashing exist in the timetable.Faculty staff needs to solve the clashing manually.This will waste time and it is a problem for staff to solve the clashing.By implement GA,clashing will be reduced.The objective of the project is to develop aprototype in scheduling application for generates an optimum timetable for a faculty.Genetic algorithm will be implemented.The scope of FTGA is Faculty of Computer Systems & Software Engineering (FCSSE).The methodology use in this project is prototype model.The testing result show 95 out of 100 test cases achieved the maximum fitness value which means there is no clashing in the timetable.The maximum generation is set to 15 generation.Population for each generation is 3 populations.Percentage of FTGA solve the problem is 95%.…”
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Undergraduates Project Papers -
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Smart Routing For Solid Waste Collection
Published 2023“…The problem of waste management in Malaysia has become increasingly complex due to an increase in waste generation and insufficient technology, manpower, and facilities. …”
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Final Year Project Report / IMRAD -
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Design of smart waste bin and prediction algorithm for waste management in household area
Published 2018“…This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Generation (SWG) based on household size factor. …”
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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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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Predicting sanitary landfill leachate generation in humid regions using ANFIS modeling
Published 2018“…Leachate generation is related to several variable factors, including meteorological data, waste generation rates, and landfill design conditions. …”
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…New algorithms, journal papers and computerized system were also developed. …”
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Monograph -
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Real-time intelligent recycle waste detection and classification using you only look once version 5 / Aiman Syafwan Amran
Published 2023“…Recycle waste is an integral part of our daily lives. It generates various type of waste materials in our homes, workplaces and communities. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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Conference or Workshop Item -
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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A greedy heuristics multiple criteria model for solving multi-landfill site selection and plant propagation algorithm for improving waste collection vehicle routing solutions
Published 2023“…This research focuses on two solid waste management (SWM) problems, particularly the landfill site selection problem (LSSP) and the waste collection vehicle routing problem (WCVRP). …”
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CNN integrated mobile application: food image recognition for recipe generation
Published 2025“…In this research, the CNN algorithm has generated a good and acceptable performance with more than 96% accuracy. …”
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Mathematical formulation of tabu search in combinatorial optimization
Published 2008“…The test instances involve five to 50 nodes systematically generated similar to the real world CARP. The newly modified RTS algorithm gives a better performance than TS and (Look-Ahead Strategy) LAS method.…”
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Monograph -
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Improved power output forecastingtechnique for effective battery management in photovoltaic system / Utpal Kumar Das
Published 2019“…In addition, a novel data preparation algorithm is also developed to prepare the solar irradiance (SI) pattern of the forecasted day for forecasting PV output power based on the online-weather-report. …”
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Development of a fuzzy multi-objective mathematical model for hazardous waste location-routing problem
Published 2014“…In this research, a fuzzy multi-objective mixed integer programming location–routing model for the hazardous waste is developed. This study considers uncertainty in generated hazardous waste quantity by using fuzzy parametric programming. …”
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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