Search Results - (( time reduction learning algorithm ) OR ( java application optimisation algorithm ))

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

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…So, the application of the theory as part of the learning models was proposed in this thesis. Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater by Khan M.S.J., Sidek L.M., Kumar P., Alkhadher S.A.A., Basri H., Zawawi M.H., El-Shafie A., Ahmed A.N.

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Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems by Mwinyi, Amir Kombo

“…The experimental results show that the improved rsync (irsync) algorithm yields a better performance against two previous algorithms, rsync algorithm and hierarchical folder synchronization algorithm (HFSA) in terms of reducing computation time and improve synchronization response time. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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Architecture for latency reduction in healthcare internet-of-things using reinforcement learning and fuzzy based fog computing by Shukla, S., Hassan, M.F., Jung, L.T., Awang, A.

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Architecture for latency reduction in healthcare internet-of-things using reinforcement learning and fuzzy based fog computing by Shukla, S., Hassan, M.F., Jung, L.T., Awang, A.

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Improving Support Vector Machine Performance using Modified Similarity Distance Plotting-Data Reduction by Abdul Muqtasid, Rushdi, Mohammad, Hossin, Norita, Norwawi

“…The results reveal that SDP-DR, especially its Mean of Each Column (MEC) variant, achieves higher accuracy and competitive reduction rates while maintaining reasonable classification times compared to other benchmark algorithms. …”
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A systematic literature review of deep learning neural network for time series air quality forecasting by Zaini N., Ean L.W., Ahmed A.N., Malek M.A.

Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection by Siti, Mujilahwati, Noor Zuraidin, Mohd Safar, Ku Muhammad Naim, Ku Khalif, Nasyitah, Ghazalli

“…Of the three deep learning models, LSTM demonstrated the highest accuracy, at 91.41%, while also exhibiting a notable reduction in computation time, approaching 50%.…”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

“…The proposed algorithms have been tested on a variety of datasets from the UCI machine learning repository. …”
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An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets by Abdul Muqtasid, Rushdi

“…The k-Nearest Neighbour (k-NN) algorithm is one of the most widely used Instance-Based Learning methods due to its simplicity and ease of implementation. …”
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Zebra optimization algorithm for feature selection by Faizan, Muhammad, Muhammad Arif, Mohamad

“…Feature selection is very important part in increasing the performance of machine learning models. This is done because of reducing the complexity of dataset, improving accuracy and lowering computation costs and time. …”
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An efficient AdaBoost algorithm for enhancing skin cancer detection and classification by Gamil, Seham, Zeng, Feng, Alrifaey, Moath, Asim, Muhammad, Ahmad, Naveed

“…To tackle these issues, researchers have explored the application of artificial intelligence (AI) tools, particularly machine learning techniques such as shallow and deep learning, to enhance the diagnostic process for skin cancer. …”
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Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System by Hormozi, Shahram Golzari

“…The experimental results show that utilizing exponential-based resource allocation methods decreases the training time and increases the data reduction capability of Artificial Immune Recognition System. …”
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Bio-signal identification using simple growing RBF-network (OLACA) by Asirvadam , Vijanth Sagayan, McLoone, Sean, Palaniappan, R

“…These algorithms are developed primarily for applications with fast sampling rate which demands significant reduction in computation load per iteration. …”
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Combination of perturb and observe with online sequential extreme learning machine for photovoltaic system maximum power point tracking by Dira, Yasir Sabah

“…From different MPPT techniques previously proposed, the online sequential extreme learning machine algorithm and conventional perturb and observe are combined together as a proposed MPPT algorithm. …”
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Progress in prediction of photocatalytic CO2 reduction using machine learning approach: A mini review by Ali, Md Mohshin, Hossen, Md. Arif, Azrina, Abd Aziz

“…These models can handle extensive experimental datasets, optimize operational parameters, and provide insights into CO2 reduction (CO2R) mechanisms. ML models also simplify the material selection, reducing experimental validation time and thereby improving the overall efficiency of PC-CO2R. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…Integrating SSA and SVM machine learning algorithms improves decision-making processes, leading to better crop yield through early detection and timely nutrient management. …”
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