Search Results - (( data optimization method algorithm ) OR ( parallel extraction using algorithm ))*
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1
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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Thesis -
2
An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…Searches within a group can be done using a half-searching algorithm to improve the response time for data retrieval. …”
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3
Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. SKF is compared with conventional algorithms for image template matching which are performance index value (PIM) and correlation by using DC components of image (TMC) and by using power of images (TMP) methods. …”
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4
Hybrid Machine Translation Using Malay-English Language Parallel Text Extraction From Comparable Text
Published 2024“…We improve the bleu score from 13.40% to 15.41% using 315,194 parallel texts. In the second problem, we propose an algorithm to extract parallel sentences and parallel fragments/subsentences from comparable texts. …”
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5
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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Final Year Project / Dissertation / Thesis -
6
A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering
Published 2023“…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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7
A parallel-model speech emotion recognition network based on feature clustering
Published 2023“…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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8
VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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9
Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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10
An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. …”
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13
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
14
Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
Published 2022“…Comparative results alongside other existing metaheuristic-based algorithms further confirmed excellence of the proposed method through its superior performance against the slime mould algorithm (SMA), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), grey wolf optimizer (GWO), and safe experimentation dynamics (SED) algorithm.…”
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Conference or Workshop Item -
15
Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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16
Data clustering using the bees algorithm
Published 2007“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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17
An improved K-nearest neighbour with grasshopper optimization algorithm for imputation of missing data
Published 2021“…Thus, this paper proposes a novel method for imputation of missing data, named KNNGOA, which optimized the KNN imputation technique based on the grasshopper optimization algorithm. …”
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18
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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19
Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail
Published 2014“…Exponential smoothing is a simple extrapolative method that seeks to identify pattern of past data. …”
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Research Reports -
20
A derivative-free optimization method for solving classification problem
Published 2010“…One of the most promising ways to data classification is based on methods of mathematical optimization. …”
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