Search Results - (( basic classification learning algorithm ) OR ( loading identification system algorithm ))
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Evolutionary Programming (EP) based technique for secure point identification with load shedding technique in power transmission / Abdul Rahman Minhat
Published 2008“…This algorithm is used to estimate the maximum loadability point in power system. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus
Published 2003“…Voltage stability problems have been one of the major concerns for electric utilities as a result of a system heavy loading. This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. …”
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Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index
Published 2023“…Electric power plant loads; Learning algorithms; MATLAB; Multiobjective optimization; Optimization; Reactive power; Back tracking; Backtracking search algorithms; Identification method; Load-shedding; Multi-objective functions; Power flow simulation; System contingencies; Under voltage load shedding; Electric load shedding…”
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Learning to filter text in forum message
Published 2005“…In this paper, the modification of the algorithm including pre-processing and classification will be discussed in the attempt to apply learning to filter forum messages.…”
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Hybrid intelligent methods for parameter identification and load frequency control in power system
Published 2014“…Where, in the first part, the coherent identification algorithm for single and multi-area power systems with disturbances is proposed. …”
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6
Email spam classification based on deep learning methods: A review
Published 2025“…The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…The approach was tested on the KDD Cup99 intrusion detection dataset and the results proved the proposed PSO-RKFLN as an accurate, reliable, and effective classification algorithm.…”
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A Novel Method for Fashion Clothing Image Classification Based on Deep Learning
Published 2023“…In recent years, using large-scale deep learning networks to achieve image recognition and classification can improve classification accuracy, such as VGG16 and Residual Network (ResNet). …”
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Review of Wheat Disease Classification and Severity Detection Models
Published 2023“…This paper mainly aims to explain deep learning-based wheat diseases identification algorithm, and to discuss the benefits and drawbacks of present wheat disease detection approaches. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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Application of system identification method coupled with evolutionary algorithms for the optimization of power consumption in a pem fuel cell propulsion system / Suhadiyana Hanapi
Published 2018“…Secondly, in this research, an empirical dynamic model of the PEM fuel cell system in vehicles was analyzed and validated using the system identification method……”
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Book Section -
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…This article describes the fundamentals of ML-based implementations, as well as future limits and concerns for the production of skin cancer detection and classification systems. We also explored five fields of dermatology using deep learning applications: (1) the classification of diseases by clinical photos, (2) der moto pathology visual classification of cancer, and (3) the measurement of skin diseases by smartphone applications and personal tracking systems. …”
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Review of deep convolution neural network in image classification
Published 2017“…The convolution neural network model trained by the deep learning algorithm has made remarkable achievements in many large-scale identification tasks in the field of computer vision since its introduction. …”
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…However, the training datasets usually compose feature sets of irrelevant or redundant information, which impacts the performance of classification, and traditional learning algorithms such as backpropagation suffer from known issues, including slow convergence and the trap of local minimum. …”
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Neural network paradigm for classification of defects on PCB
Published 2003“…A new technique is proposed to classify the defects that could occur on the PCB using neural network paradigm. The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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Embedded Meta evolutionary-firefly algorithm-ANN for multi dg planning in distribution system / Siti Rafidah Abdul Rahim
Published 2019“…The voltage dependent load has a main impact on distribution system planning studies. …”
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Application of Genetic Algorithm for the Reduction of Reactive Power Losses in Radial Distribution System
Published 2006“…ERACS is used to perform load flow analysis while MATLAB is used for the identification of capacitor current via GAtool, and algorithm for the calculation of loss savings, its particular capacitor size and location. …”
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Surface Normals with Modular Approach and Weighted Voting Scheme in 3D Facial Expression Classification
Published 2014“…We constructed a Weighted Voting Scheme (WVS) to infer the emotion underlying a collection of modules using a weight that is determined using the AdaBoost learning algorithm. Our results indicate that using 3DFSN as the feature vector of WVS yields a better performance than 3D facial points and 3D facial distance measurements in facial expression classification using both WVS and a Majority Voting Scheme (MVS). …”
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