Search Results - (( development training waste algorithm ) OR ( java implication based algorithm ))

IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management by Eugine Teh, Yin Jie, Chee Soon, Chong, Rozaimi, Ghazali, Hazriq Izzuan, Jaafar, Muhamad Fadli, Ghani, Howe Cheng, Teng, Nur Farhanah, Zulkipli, Siaw Hong, Liew

“…Advanced data preprocessing, such as augmentation and normalization, ensures robust model training, while optimized algorithms guide waste sorting based on classification results. …”
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Recyclable waste classification using YOLO-based Convolutional Neural Network (CNN) / Shaharil Armin Sharizal by Sharizal, Shaharil Armin

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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant by Chun T.S., Malek M.A., Ismail A.R.

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Optimization of food waste to sewage sludge ratio for anaerobic co-digestion process using Artificial Neural Network (ANN) and Genetic Algorithm (GA) by Mansor, Mariatul Fadzillah, Jamaludin, Nurul Syazwana, Tajuddin, Husna Ahmad

“…Food waste is a major global issue especially in developed countries. …”
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Mixed waste classification based on vision inspection / Hassan Mehmood Khan by Hassan Mehmood , Khan

“…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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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

“…The proposed dataset offers a unique resource for researchers to train machine learning models for plastic waste detection. …”
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Operator Training Simulator Using Plantwide Control for Biodiesel Production from Waste Cooking Oil by Shikchand Patle, Dipesh

“…On-job training is often costly, risky and incomplete as some emergency situations may not arise during the training session. …”
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Automation of plastic waste sorting through robotic technology by Chong, Yoong Kiat

“…A YOLOv8 deep learning model, trained on a custom dataset of waste images, was integrated with the ByteTrack algorithm to provide real-time object detection and tracking. …”
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Development of airbag suit system for motorcyclist by Zainal Abidin, Zulkifli, Razali, Fakhruddin

“…The project involved development of a control algorithm for the airbag inflation and performing analysis on the finished prototype. …”
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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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Predicting sanitary landfill leachate generation in humid regions using ANFIS modeling by Abunama, Taher, Othman, Faridah, Younes, Mohammad K.

“…The best model structure consisted of two triangular fuzzy membership functions and a hybrid training algorithm with eight fuzzy rules. The proposed ANFIS model showed a good performance with an overall correlation coefficient of 0.952.…”
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Genetic algorithm optimization of product design for environmental impact reduction / Julirose Gonzales by Julirose , Gonzales

“…The aim of this research is to develop a methodology that will aid designers to reduce the potential environmental impact of a product’s design, which does not require them to train additional skills in environmental impact analysis. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Design And Development Of Path Planning Techniques For A Tennis Ball Retriever Robot by Chee, Kiang Lam, Ali, Mohanad Faeq, Lam, C. K., K.V. Ch’ng, Sundaraj, Kenneth, Tan, Wen Hong

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

“…The input and output of the RSM design was used in artificial neural networks for training purpose. 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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Sales prediction for Adha Station by using predictive analytics by Mohd Mokhid, Muhammad Amier Latieff

“…In the future, it is advisable to collect additional contextual information, such as a compilation of public holidays and promotions, implement realtime modifications, evaluate more advanced algorithms and enhance staff training and data literacy. …”
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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.

“…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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PREDICTIVE MODELING OF DIMENSIONAL ACCURACIES IN 3D PRINTING USING ARTIFICIAL NEURAL NETWORK by Sivaraos, Kumaran K., Dharsyanth R., Amran M., Shukor S.M., Pujari S., Ramasamy D., Vatesh U.K., Mahdi Al-Obaidi A.S.H., Ramesh S., Lee K.Y.S.

“…Experimental data consisting of 27 sets of control parameters and corresponding dimensional outputs were used to train and validate the ANN model. The ANN model was developed using MATLAB software, employing training functions and learning algorithms to optimize the neural network architecture. …”

Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (AN... by Onyelowe, K. C., Alaneme, G. U., Onyia, M. E., Bui Van, D., Dimonyeka, M. U., Nnadi, E., Ogbonna, C., Odum, L. O., Aju, D. E., Abel, C., Udousoro, I. M., Onukwugha, E.

“…For the ANN model, feed forward back propagation and Levernberg Marquardt training algorithm were utilized for the model development with the optimized network architecture of 8-6-3 derived based on MSE performance criteria; while for the fuzzy logic model, the mamdani FIS with both triangular and trapezoidal membership function with both models formulated, simulated and computed using MATLAB toolbox. …”
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