Search Results - (( intelligence based training algorithm ) OR ( intelligence sets based algorithm ))
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. ANN is a computer-based simulation of the living nervous system which works quite differently from conventional programming. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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Embedded Artificial Intelligent (AI) To Navigate Cart Follower
Published 2018“…The training algorithm may also vary with different sets of parameters, number of neurons and activation function. …”
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Monograph -
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An Empirical Evaluation of Artificial Intelligence Algorithm for Hand Posture Classification
Published 2022“…In this connection, a recent dataset, â��Mocap Hand Postures Data Set,â�� has been opted to employ the different variants of the machine learning algorithm. …”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…However the proposed algorithm offers a promising approach to building intelligent systems.…”
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Final Year Project -
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A Novel Path Prediction Strategy for Tracking Intelligent Travelers
Published 2009“…The FCM nodes are a novel selection of kinematical factors. Genetic algorithm (GA) is then used to train the FCM to be able to replicate the decisional behaviors of the intelligent traveler. …”
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…The stacked ensemble method uses several heterogeneous deep neural networks as the base learners. During the training and optimization process, these base learners adopt a hybrid BP and Particle Swarm Optimization algorithm to combine both local and global optimization capabilities for identifying optimal features and improving the classification performance. …”
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Development of hybrid artificial intelligent based handover decision algorithm
Published 2017“…Hence, in this paper, the development of novel hybrid artificial intelligent handover decision algorithm has been developed. …”
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Domestic garbage target detection based on improved YOLOv5 algorithm
Published 2023“…Experiments have proved that the accuracy of intelligent classification reached 98.27%, which is 3.85% higher than the original algorithm. …”
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Conference or Workshop Item -
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Prediction of Optimum Cutting Conditions in Dry Turning Operations of S45C Mild Steel using AIS and PSO Intelligent Algorithm
Published 2014“…The suggested system is based on Particle Swarm Optimization (PSO) and Artificial Immune System (AIS) intelligent algorithms. …”
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A layer-sensitivity based artificial neural network for characterization of oil palm fruitlets
Published 2021“…To further investigate the generalization ability of the trained neural network, three other neural network training algorithms were deployed for the same dataset. …”
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Predicting Diseases Using Multi-BackPropagation
Published 2002“…On the other hand, based on 256 data sets the network takes 2,459,172,864 milliseconds to complete the learning. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Conference or Workshop Item -
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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Processing time estimation in precision machining industry using AI / Lim Say Li
Published 2017“…Neural Network (NN) model is chosen as the artificial intelligence approach used in this research. Levenberg-Marquardt algorithm is used as the training algorithm. …”
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Artificial neural networks based optimization techniques: A review
Published 2023“…The entire set of such techniques is classified as algorithms based on a population where the initial population is randomly created. …”
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