Search Results - (( data evaluation max algorithm ) OR ( parallel extraction method algorithm ))
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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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Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network
Published 2014“…To conclude, multi objective parallel genetic algorithm can automatically tune feed forward neural network to classify the dataset with a good classification rate.…”
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5
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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8
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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9
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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10
An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. …”
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Robust partitioning and indexing for iris biometric database based on local features
Published 2018“…The proposed method combines three transformation methods DCT, DWT and SVD to analyse iris images and extract their local features. …”
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Combining deep and handcrafted image features for MRI brain scan classification
Published 2019“…In parallel, handcrafted features are extracted using the modified gray level co-occurrence matrix (MGLCM) method. …”
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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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Thesis -
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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 -
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Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui
Published 2016“…Parallel imaging is a robust method for accelerating the data acquisition in Magnetic Resonance Imaging (MRI). …”
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A new multi-frames watermarking technique for tamper detection and recovery
Published 2017“…The sequential multi-frames watermarking process could be speed up by two methods, first method was designed a speedy watermarking scheme algorithm (ROI-DR) in a single frame of medical image, and the second method was developed a new multi-frames watermarking scheme by adding parallelism component into sequential multi-frames watermarking process. …”
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