Search Results - (( parameter extraction utilizing algorithm ) OR ( parameter optimization based algorithm ))
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Individual-tree segmentation and extraction based on LiDAR point cloud data
Published 2024“…The objective was to identify the optimal parameters for both algorithms in terms of tree height extraction precision. …”
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Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphson methods
Published 2022“…Extraction of the photovoltaic (PV) model parameters is critical for forecasting these systems’ energy output. …”
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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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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination
Published 2022“…In this work, a new improved arithmetic optimization method based on the adaption of Newton–Raphson and Levenberg–Marquardt damping parameter (IAOANRaLMp) is presented to globally extract the parameter of the single- and double-diode PV models. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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Evaluation of genetic algorithm based solar tracking system for photovoltaic panels
Published 2008“…In this paper, a genetic algorithm (GA) has been proposed utilizing sun tracking approaches to maximize the performance of PV panels. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network
Published 2006“…The back propagation algorithm was adopted for this study. The optimal model for predicting missing data found in this study is the network with the combination of learning rate and the number of neurons in the hidden layer of 0.2 and 60. …”
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Final Year Project Report / IMRAD -
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Improved power output forecastingtechnique for effective battery management in photovoltaic system / Utpal Kumar Das
Published 2019“…A PSO-based algorithm is adopted for the appropriate selection of dominated parameters of SVR-based model to achieve better performance. …”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…The accuracy of BFS calculated based on LCF is highly dependable on the initial parameter setting of the curve fitting process. …”
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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“…Several conventional adaptive distance relay (ADR) and computational based intelligent modifications presented to solve the impending compromise by using faulted line voltage and current parameters for the various protection relay controller modification, optimizing synchronized measurement to block or limit the fault current penetration into the grid. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…Next, an advanced machine learning based on is utilized to predict islanding and none islanding states. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
Published 2021“…Apart from that, having low values in four of the performance criteria: RMSE, MAE, NSE, and RSR, have further strengthened the credibility of the results. As for the optimization process, the reservoir operation rule was derived using a meta-heuristic algorithm at the monthly interval. …”
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Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems
Published 2025“…The key attributes that establish the classification learning sessions are the channel parameters extracted from the ray tracing generated multipath signals. …”
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High impedance fault detection and localization in 11kV distribution system / Mohd Syukri Ali
Published 2018“…In this process, the grey wolf optimization (GWO) technique is adopted in order to provide the optimal value of ANN parameters. …”
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Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics
Published 2024“…In the map phase, the statisticalfeatures and the Principal Component Analysis (PCA) features are extracted. In the reduction phase, the optimal features are selected with theaid of the developed Hybrid Flower Pollination Bumblebees Optimization Algorithm (HFPBOA). …”
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…For classification performances, optimization of machine learning parameters and exploration of deep learning approaches can be applied for further enhancement.…”
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