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1
Maximum 2-satisfiability in radial basis function neural network
Published 2020“…In this study, the effectiveness of RBFNN-MAX2SAT can be estimated by evaluating the proposed models with testing data sets. …”
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A New Algorithm For Prediction WIMAX Traffic Based On Artificial Neural Network Models
Published 2024“…These data are available from LibyaMax network (WiMAX technology) motorized by Libya Telecom and Technology over a period of 90 days. …”
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WiMAX Traffic Forecasting Based On Artificial Intelligence Techniques
Published 2024thesis::doctoral thesis -
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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5
Modern fuzzy min max neural networks for pattern classification
Published 2019“…To build an efficient classifier model, researchers have introduced hybrid models that combine both fuzzy logic and artificial neural networks. Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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6
Analysis of WiMAX Positioning Using Received- Signal-Strength Method
Published 2013“…By the performance evaluation, the user can plan better simulation system and can create more accurate algorithms for radio positioning.…”
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Artificial neural network-salp-swarm algorithm for stock price prediction
Published 2024“…The effectiveness of the SSA-ANN model is evaluated using the Yahoo stock price dataset. The results show that the SSA-ANN model outperforms other models when applied to normalized data. …”
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Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting
Published 2021“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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10
M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)
“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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Monograph -
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Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
12
Reactive memory model for ant colony optimization and its application to TSP
Published 2014“…The performances of six (6) ant colony optimization variants were evaluated to select the base for the proposed model.Based on the results, Max-Min Ant System has been chosen as the base for the modification.The modified algorithm called RMMAS, was applied to TSPLIB95 data and results showed that RMMAS outperformed the standard MMAS.…”
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Conference or Workshop Item -
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The effect of data preprocessing on the performance of artificial neural networks techniques for classification problems
Published 2012“…It is known as an excellent classifier of nonlinear input and output numerical data. Improving training efficiency of ANN based algorithm is an active area of research and numerous papers have been reviewed in the literature. …”
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14
Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud
Published 2022“…Nowadays, there are numerous license plate recognition systems that have been developed and analysed effectively by previous researchers using different machine learning algorithms. However, according to a recent study, ANN algorithms require a huge amount of training data while BPFFNN algorithms only have an average success rate of 70% in recognizing all the characters. …”
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Embedded Artificial Intelligent (AI) To Navigate Cart Follower
Published 2018“…The training algorithm may also vary with different sets of parameters, number of neurons and activation function. …”
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16
Self-calibration algorithm for a pressure sensor with a real-time approach based on an artificial neural network
Published 2018“…To verify the proposed model’s capability to build a self-calibration algorithm, the model was tested using an untrained input data set. …”
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Vehicular ad-hoc network (vanets) for electrical vehicle charging management
Published 2025text::Thesis -
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Face anti-spoofing using Convolutional Neural Networks / Siti Nurul Izzah Bahrain
Published 2024“…This project is due to its ability to do face detection and anti-spoofing tasks and handle high-dimensional data. The study investigates CNN requirements, develops a prototype system, and evaluates its accuracy, achieving an impressive 86% accuracy in detecting fake facial appearances. …”
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Real time self-calibration algorithm of pressure sensor for robotic hand glove system
Published 2019“…The model was tested using an untrained input data set in order to verify the Proposed model’s capability for implementing a self-calibration algorithm. …”
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20
Comparative Analysis of Pneumonia Detection from Chest X-Ray Images Using CNN And Transfer Learning
Published 2024“…Keywords: Pneumonia, Chest X-ray, Deep Learning, Convolutional Neural Network (CNN), Mobile Net, VCG, ReLU, Max pooling.…”
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