Search Results - (( using optimization based algorithm ) OR ( knowledge extraction using algorithm ))
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Multilingual Sentiment Analysis From Students Feedback: Optimal Techniques And Resources For Bengali Lingual Data
Published 2024thesis::doctoral thesis -
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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3
Development of deep reinforcement learning based resource allocation techniques in cloud radio access network
Published 2022“…The first proposed algorithm aims to optimize the EE by controlling the on/off status of RRH via a deep Q network (DQN) and subsequently solving a power optimization problem. …”
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Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm
Published 2023“…In reducing the learning complexity, a genetic algorithm was implemented to optimize the logical rule throughout the learning phase in performing a 2-satisfiability-based reverse analysis method, implemented during the learning phase as this method was compared. …”
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Improved Malware detection model with Apriori Association rule and particle swarm optimization
Published 2019“…These rule models are used together with extraction algorithm to classify and detect malicious android application. …”
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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems
Published 2021“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…Experimentally observed responses were used to train, map and optimize the network algorithms before the best architecture was selected. …”
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Integration of knowledge-based seismic inversion and sedimentological investigations for heterogeneous reservoir
Published 2020“…The porosity model obtained by conventional method in previous step would be used for primary evaluation of the rules. The extracted rules and optimized number rules then would be used for rule-based porosity estimation. …”
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Dynamic modelling of proton exchange membrane fuel cell system for electric bicycle / Azadeh Kheirandish
Published 2016“…Recent models provide high accuracies using complex systems and complicated calculations using advanced optimization algorithms. …”
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11
The exploration of hybrid metaheuristics-based approaches: A bibliometric analysis
Published 2025“…The rapid evolution of computational intelligence has driven significant interest in hybrid metaheuristics, which combine multiple optimization algorithms to solve complicated problems more efficiently. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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P300 detection of brain signals using a combination of wavelet transform techniques
Published 2012“…In this research the BCI competition data-set has been processed through 5 optimized detection methods. Wavelet transform (WT), student’s two-sample t-statistic (T-Test) and support vector machines (SVM) used in designing the algorithms. …”
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15
Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri
Published 2025“…This work presents a novel graph-based semi-supervised learning (GSSL) algorithm designed for wafer defect detection. …”
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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal
Published 2019“…Lastly, the incremental learning algorithm ABACOC is used to classify each feature of food classes. …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The hybrid discrete wavelet multiresolution analyses and machine learning (DWMRA-ML) algorithm is deployed to discover the hidden useful knowledge extraction from the 1-cycle short circuit transient fault signals (voltage and current) from healthy and fault lines section. …”
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Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues
Published 2024“…Here, we also proposed pipelines based on a predictive model using statistical and machine learning algorithms to accurately differentiate colorectal adenocarcinoma and polyp patients from normal individuals. …”
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Statistical band selection for descriptors of MBSE and MFCC-based features for accent classification of Malaysian English / Yusnita M. A. ...[et al.]
Published 2013“…A simple algorithm to select bands so called statistical band selection (SBS) method using smallest variances within class scores was developed to optimize the presentation of speech features. …”
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