Search Results - (( based optimization modified algorithm ) OR ( using vectorization based algorithm ))
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…Based on the acquired results, the experiments reveal that the modified word vectors algorithm can effectively alter original LLM-generated word vectors to reflect intended contexts and can outperform baseline scores in contextual text classification tasks. …”
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Thesis -
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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Optimization of neural network through genetic algorithm searches for the prediction of international crude oil price based on energy products prices
Published 2014“…This study investigated the prediction of crude oil price based on energy product prices using genetically optimized Neural Network (GANN). …”
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Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…Purpose – The purpose of the research is to solve Travelling Salesman Problem (TSP) using Simulated Kalman Filter (SKF) algorithm and single-solution SKF (ssSKF) algorithm based on numerical ordering technique. …”
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Smoothed functional algorithm with norm-limited update vector for identification of continuous-time fractional-order Hammerstein Models
Published 2024“…In particular, the standard smoothed functional algorithm (SFA) based method is modified by implementing a limit function in the update vector of the standard SFA based method to solve the issue of high tendency of divergence during the identification process. …”
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Evaluation of Vector Evaluated Particle Swarm Optimisation Enhanced with Non-dominated Solutions and Multiple Nondominated Leaders based on WFG Test Functions
Published 2014“…Multi Objective Optimisation (MOO) problem involves simultaneous minimization or maximization of many objective functions. One of MOO algorithms is Vector Evaluated Particle Swarm Optimization (VEPSO) algorithm. …”
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An enhanced support vector regression -African Buffalo optimisation algorithm for electricity time series forecasting
Published 2023“…Evaluated using benchmark datasets, SVR-eABO achieves high accuracy, surpassing standard SVR and other optimization-based SVR variants like SVR-PSO, SVR-ABC, SVR-CS, and SVR-GA. …”
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An Improved Wavelet Neural Network For Classification And Function Approximation
Published 2011“…Second, the proposed enhanced fuzzy c-means clustering algorithm—specifically, the modified point symmetry-based fuzzy c-means (MPSDFCM) algorithm—was employed in selecting the locations of the translation vectors of the WNN. …”
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…The mean closure performance of the BSCCH algorithm is compared against seven selected state-of-the-art algorithms, namely Differential Evolution with Adaptive Trial Vector Generation Strategy and Cluster-replacement-based Feasibility Rule (CACDE), Improved Teaching Learning Based Optimization (ITLBO), Modified Global Best Artificial Bee Colony (MGABC), Stochastic Ranking Differential Evolution (SRDE), Novel Differential Evolution (NDE), Partical Swarm Optimization for solving engineering problems-a new constraint handling mechanism (CVI-PSO) and Ensemble of Constraint Handling Techniques (ECHT). …”
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Robust correlation feature selection based support vector machine approach for high dimensional datasets
Published 2025“…The third step employs the support vector machine algorithm to calculate prediction values. …”
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SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique
Published 2023Conference Paper -
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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Reliable multiclass cancer classification of microarray gene expression profiles using an improved wavelet neural network
Published 2011“…Second, the proposed enhanced fuzzy c-means clustering algorithm—specifically, the modified point symmetry-based fuzzy c-means (MSFCM) algorithm—was employed in selecting the locations of the translation vectors of the WNN. …”
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Facial emotion detection using Guided Particle Swarm Optimization (GPSO)
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Working Paper -
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…Hence, it is required to develop effective imbalanced LR-based methods to be widely used in data mining applications. …”
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Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO
Published 2017“…This paper presents an improved wave kernel signature (WKS) using the modified particle swarm optimization (MPSO)-based intelligent recognition and matching on 3D shapes. …”
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