Search Results - Back selection algorithm
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WCBP: A new water cycle based back propagation algorithm for data classification
Published 2016“…The performance of the proposed Water Cycle based Back-Propagation (WCBP) algorithm is compared with the conventional BPNN, ABC-BP and ABC-LM algorithms on selected benchmark classification problems from UCI Machine Learning Repository. …”
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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network
Published 2020“…Thus, this paper proposed metaheuristic algorithms such as Particle Swarm Optimization, Ant Colony Algorithm and Harmony Search Algorithm based feature selection to identify the most significant features of skeleton remains. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…In the proposed HACPSO algorithm, initially accelerated particle swarm optimization (APSO) algorithm searches within the search space and finds the best sub-search space, and then the CS selects the best nest by traversing the sub-search space. …”
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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
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Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network
Published 2015“…The method involves selecting the architecture, network parameters, training algorithm, and model validation. …”
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Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques
Published 2024“…Fuzzy arithmetic operations on fuzzy numbers and artificial neural networks with a back-propagation learning algorithm were used to represent the structure of the neuro-fuzzy risk assessment model, whereas genetic algorithms were used to develop the safe path selection model. …”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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Improvement of adaptive GAs and back propagation ANNs performance in condition diagnosis of multiple bearing system using grey relational analysis
Published 2014“…Condition diagnosis of multiple bearings system is one of the requirements in industry field, because bearings are used in many equipment and their failure can result in total breakdown.Conditions of bearings commonly are reflected by vibration signals data.In multiple bearing condition diagnosis, it will involve many types of vibration signals data; thus, consequently, it will involve many features extraction to obtain precise condition diagnosis.However, large number of features extraction will increase the complexity of the diagnosis system.Therefore, in this paper, we presented a diagnosis method which is hybridization of adaptive genetic algorithms (AGAs), back propagation neural networks (BPNNs), and grey relational analysis (GRA) to diagnose the condition of multiple bearings system.AGAs are used in the diagnosis algorithm to determine the best initial weights of BPNNs in order to improve the diagnosis accuracy.In addition, GRA is applied to determine and select the dominant features from the vibration signal data which will provide good diagnosis of multiple bearings system in less features extraction.The experiments results show that AGAs-BPNNs with GRA approaches can increase the accuracy of diagnosis in shorter processing time, compared with the AGAs-BPNNs without the GRA.…”
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Improvement of adaptive GAs and Back propagation ANNs performance in condition diagnosis of multiple bearing system using grey relational analysis
Published 2014“…AGAs are used in the diagnosis algorithm to determine the best initial weights of BPNNs in order to improve the diagnosis accuracy.In addition, GRA is applied to determine and select the dominant features from the vibration signal data which will provide good diagnosis of multiple bearings system in less features extraction.The experiments results show that AGAs-BPNNs with GRA approaches can increase the accuracy of diagnosis in shorter processing time, compared with the AGAs-BPNNs without the GRA.…”
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Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model
Published 2001“…In this paper, major properties of an adaptive fuzzy model as a system identifier when trained by the back-propagation algorithm are discussed. The standard rule-based fuzzy models were used to identify discrete-time nonlinear dynamic systems. …”
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Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…To validate the finite element model physical experiments were conducted. A neural network algorithm based on the backpropagation algorithm has been developed. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…ANN based STLF models commonly use back-propagation algorithm, which generally exhibits a slow and improper convergence that affects the forecast accuracy. …”
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Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh
Published 2019“…The best result achieved for Pb2+ removal using ANFIS algorithm is with RE 7.078%. For As3+ removal using different adsorbents, two algorithms were applied for the modelling, the feed-forward back-propagation maximum RE achieved is 5.97% while, the NARX algorithm achieved better accuracy with maximum RE of 5.79%. …”
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Modelling of Elastic Modulus Degradation in Sheet Metal Forming Using Back Propagation Neural Network
Published 2015“…The method involves selecting the architecture, network parameters, training algorithm, and model validation. …”
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An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…Back Propagation (BP) has proven to be a robust algorithm for different connectionist learning problems which commonly available for any functional induction that provides a computationally efficient method. …”
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Early detection of dengue disease using extreme learning machine
Published 2018“…Therefore, the proposed ELM model can be considered as an alternative algorithm to apply for early detection of Dengue disease.…”
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An Efficient Solution to Travelling Salesman Problem using Genetic Algorithm with Modified Crossover Operator
Published 2019“…The efficiency of the proposed algorithm is compared to the classical genetic algorithm. …”
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Performance of various training algorithms on scene illumination classification
Published 2015“…The increasing number of training algorithms along with their convincing results will make this question that which algorithm will be more efficient. …”
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