Search Results - (( developing learning waste algorithm ) OR ( java implementation ant algorithm ))

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  1. 1

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…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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    Thesis
  2. 2

    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
    “…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
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    Article
  3. 3

    Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia by Latif S.D., Hazrin N.A.B., Younes M.K., Ahmed A.N., Elshafie A.

    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. …”
    Article
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    An Embedded Machine Learning-Based Spoiled Leftover Food Detection Device for Multiclass Classification by Wan Azman,, Wan Nur Fadhlina Syamimi, Ku Azir, Ku Nurul Fazira, Mohd Khairuddin, Adam

    Published 2024
    “…In conclusion, the work demonstrates a novel method for using machine learning algorithms to classify, identify, and predict the contamination level of leftover cooked food, contributing to reducing food waste generated primarily by Malaysians…”
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    Article
  6. 6

    RGB and RGNIR image dataset for machine learning in plastic waste detection by Owen Tamin, Ervin Gubin Moung, Jamal Ahmad Dargham, Samsul Ariffin Abdul Karim, Ashraf Osman Ibrahim Elsayed, Nada Adam, Hadia Abdelgader Osman

    Published 2025
    “…However, developing an efficient machine learning model requires a comprehensive dataset with information on the size, shape, colour, texture, and other features of plastic waste. …”
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    Predicting the rutting parameters of nanosilica/waste denim fiber composite asphalt binders using the response surface methodology and machine learning methods by Al-Sabaeei, Abdulnaser M., Alhussian, Hitham, Abdulkadir, Said Jadid, Giustozzi, Filippo, Mohd Jakarni, Fauzan, Md Yusoff, Nur Izzi

    Published 2023
    “…This study evaluates and compares the feasibility of using the response surface methodology (RSM) and machine learning (ML) methods to predict the shear strain, accumulated shear strain, non-recoverable creep compliance (Jnr), and percentage of recovery (%R) of the base binder, nanosilica (NS)- modified, waste denim fiber (WDF)-modified, and NS/WDF composite asphalt binders. …”
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  11. 11

    Automation of plastic waste sorting through robotic technology by Chong, Yoong Kiat

    Published 2025
    “…This project presents the design, development, fabrication and evaluation of an automated waste sorting system integrating computer vision, robotic actuation and electronic control. …”
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    Final Year Project / Dissertation / Thesis
  12. 12

    Mixed waste classification based on vision inspection / Hassan Mehmood Khan by Hassan Mehmood , Khan

    Published 2022
    “…Classification of dry waste garbage is crucial since incorrect labelling of dry waste types may contribute huge loss to waste industry. …”
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  13. 13

    The predictive machine learning model of a hydrated inverse vulcanized copolymer for effective mercury sequestration from wastewater by Ghumman, A.S.M., Shamsuddin, R., Abbasi, A., Ahmad, M., Yoshida, Y., Sami, A., Almohamadi, H.

    Published 2024
    “…A predictive machine learning model was also developed to predict the amount of mercury removed () using GPR, ANN, Decision Tree, and SVM algorithms. …”
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    Article
  14. 14

    Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption by Zamani, Seyed Ali

    Published 2015
    “…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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    Thesis
  15. 15

    CNN integrated mobile application: food image recognition for recipe generation by Nor Azlan Shah, Muhammad Imran, Norlina Mohd Sabri, Norlina, Tan, Gloria Jennis, Zhang, Zhiping

    Published 2025
    “…This research has shown how machine learning, mobile development, and user-centric design can be successfully combined to create a useful tool for contemporary culinary demands. …”
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  16. 16

    Sales prediction for Adha Station by using predictive analytics by Mohd Mokhid, Muhammad Amier Latieff

    Published 2025
    “…This research presented a technique for projecting sales utilising current data through a machine learning algorithm. The CRISP-DM approach was employed to execute the project across the phases of business understanding, data preparation, modelling, assessment, and deployment. …”
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    Student Project
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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.

    Published 2017
    “…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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    Thesis
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    Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques by Chong, Xiao Wei

    Published 2024
    “…To address these challenges, this project proposes an innovative solution that leverages computer vision and machine learning techniques. By employing the state-of-the-art You Only Look Once (YOLO) v7 object detection algorithm, the project aims to develop a system capable of accurately detecting and classifying prawns based on their growth stages. …”
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    Final Year Project / Dissertation / Thesis
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    Digital assistant for workspace apps by See, Ling Xuan

    Published 2022
    “…The proposed system will be achieved by applying machine learning to train the digital assistant model for it can study and execute every Teams’ function or the function combinations and allow user customization on its steps to complete certain task. …”
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    Final Year Project / Dissertation / Thesis