Search Results - (( its application a algorithm ) OR ( _ modification learning algorithm ))
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Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems
Published 2011“…Over the years, many improvements and modifications of the back propagation learning algorithm have been reported. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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3
Three-term backpropagation algorithm for classification problem
Published 2006“…Standard Backpropagation Algorithm (BP) is a widely used algorithm in training Neural Network that is proven to be very successful in many diverse application. …”
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4
Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets
Published 2021“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…Secondly, the application and modification of a Jaya algorithm to deal with different OPF problems is presented. …”
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Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…Simulated Kalman Filter (SKF) solves optimization problems by finding the estimate of the optimum solution. As a multi-agent algorithm, every agent in the population acts as a Kalman filter by using a standard Kalman filter framework, which includes a simulated measurement process and a best-so-far solution as a reference. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques
Published 2011“…The proposed algorithm employs a combined model that uses two different measures (nonconformity metric measures and Local Distance-based Outlier Factor (LDOF)) to improve its detection ability. …”
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9
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. Multiple modifications are carried out on the conventional back-propagation (BP) algorithm such as, improvements in the momentum factor and adaptive learning rate. …”
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10
Unified neural network controller of series active power filter for power quality problems mitigation
Published 2013“…First, Widrow-Hoff algorithm is examined and its constant learning rate is modified by adding an adaptive learning rule to change the learning rate value. …”
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11
Enhanced extreme learning machine for general regression and classification tasks
Published 2020“…Despite its popularity, ELM has a number of challenges worth to investigating for improving the usability of ELM in a more advanced application. …”
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12
Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications
Published 2025“…To address this challenge, the paper proposed XGB5hmC, a machine learning algorithm based on a robust gradient boosting algorithm (XGBoost), with different residue based formulation methods to identify 5hmC samples. …”
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Enhancing classroom engagement using real-time student attention monitoring with YOLOv9
Published 2024“…Future enhancements will focus on integrating additional data sources, reducing misclassifications, and improving algorithm scalability and accuracy to foster a more adaptive learning environment and showcase the system's potential for diverse educational applications.…”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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Predicting factors of library traffic for UiTMCTKKT Cendekiawan Library using predictive analytics / Azzatul Husna Abdul Aziz
Published 2025“…All experts agreed on the dashboard’s ease of use, effectiveness, and efficiency, noting its clear organization and pleasant interface. They proposed a few minor modifications like improving visualizations and adjusting guidelines for better clarity. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…In keeping with this limitation, this study proposes a new variant of BH through two different modifications on the original BH. The first modification is the integration of BH algorithm and levy flight, which result in data clustering method, namely “Levy Flight Black Hole (LBH)”. …”
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19
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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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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