Acoustic emission(AE)is a nondestructive real-time monitoring technology,which has been proven to be a valid way of monitoring dynamic damage to *** classification and recognition methods of the AE signals of the roto...
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Acoustic emission(AE)is a nondestructive real-time monitoring technology,which has been proven to be a valid way of monitoring dynamic damage to *** classification and recognition methods of the AE signals of the rotor are mostly focused on machine *** that the huge success of deep learning technologies,where the Recurrent Neural Network(RNN)has been widely applied to sequential classification tasks and Convolutional Neural Network(CNN)has been widely applied to image recognition tasks.A novel three-streams neural network(TSANN)model is proposed in this paper to deal with fault detection *** on residual connection and attention mechanism,each stream of the model is able to learn the most informative representation from Mel Frequency Cepstrum Coefficient(MFCC),Tempogram,and short-time Fourier transform(STFT)spectral *** results show that,in comparison with traditional classification methods and single-stream CNN networks,TSANN achieves the best overall performance and the classification error rate is reduced by up to 50%,which demonstrates the availability of the model proposed.
In this paper, we consider distributed Independent Component Analysis (ICA) in wireless networks, where data from several geographically distributed wireless nodes (nodes) must be transmitted to a central server (serv...
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Orthogonal time frequency space (OTFS) is envisioned as a highly promising modulation technique due to its superior performance in high-mobility scenarios. Meanwhile, non-orthogonal multiple access (NOMA) stands out a...
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This paper introduces an AC stochastic optimal power flow(SOPF)for the flexibility management of electric vehicle(EV)charging pools in distribution networks under *** AC SOPF considers discrete utility functions from ...
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This paper introduces an AC stochastic optimal power flow(SOPF)for the flexibility management of electric vehicle(EV)charging pools in distribution networks under *** AC SOPF considers discrete utility functions from charging pools as a compensation mechanism for eventual energy not served to their charging *** application of the AC SOPF is described where a distribution system operator(DSO)requires flexibility to each charging pool in a day-ahead time frame,minimizing the cost for flexibility while guaranteeing technical *** areas are defined for each charging pool and calculated as a function of a risk parameter involving the uncertainty of the *** show that all players can benefit from this approach,i.e.,the DSO obtains a riskaware solution,while charging pools/tasks perceive a reduction in the total energy payment due to flexibility services.
Non-linear loads insert harmonics into the electrical power system. Harmonic frequencies in an electrical network are a foremost cause for introducing issues in the quality of power. Most of the power quality troubles...
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As a crucial data preprocessing method in data mining,feature selection(FS)can be regarded as a bi-objective optimization problem that aims to maximize classification accuracy and minimize the number of selected *** c...
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As a crucial data preprocessing method in data mining,feature selection(FS)can be regarded as a bi-objective optimization problem that aims to maximize classification accuracy and minimize the number of selected *** computing(EC)is promising for FS owing to its powerful search ***,in traditional EC-based methods,feature subsets are represented via a length-fixed individual *** is ineffective for high-dimensional data,because it results in a huge search space and prohibitive training *** work proposes a length-adaptive non-dominated sorting genetic algorithm(LA-NSGA)with a length-variable individual encoding and a length-adaptive evolution mechanism for bi-objective highdimensional *** LA-NSGA,an initialization method based on correlation and redundancy is devised to initialize individuals of diverse lengths,and a Pareto dominance-based length change operator is introduced to guide individuals to explore in promising search space ***,a dominance-based local search method is employed for further *** experimental results based on 12 high-dimensional gene datasets show that the Pareto front of feature subsets produced by LA-NSGA is superior to those of existing algorithms.
Load scheduling plays a vital role in the home energy management systems. The main objective of this load scheduling is to balance the power demand and supply power without degrading the performance of the loads and c...
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In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause *** technique rising on daily basis for detecting illness in mag...
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In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause *** technique rising on daily basis for detecting illness in magnetic resonance through pictures is the inspection of ***(computerized)illness detection in medical imaging has found you the emergent region in several medical diagnostic *** diseases that cause death need to be identified through such techniques and technologies to overcome the mortality *** brain tumor is one of the most common causes of *** have already proposed various models for the classification and detection of tumors,each with its strengths and weaknesses,but there is still a need to improve the classification process with improved effi***,in this study,we give an in-depth analysis of six distinct machine learning(ML)algorithms,including Random Forest(RF),Naïve Bayes(NB),Neural Networks(NN),CN2 Rule Induction(CN2),Support Vector Machine(SVM),and Decision Tree(Tree),to address this gap in improving *** the Kaggle dataset,these strategies are tested using classification accuracy,the area under the Receiver Operating Characteristic(ROC)curve,precision,recall,and F1 Score(F1).The training and testing process is strengthened by using a 10-fold cross-validation *** results show that SVM outperforms other algorithms,with 95.3%accuracy.
In modern process industries, maintaining precise weight measurements is critical for ensuring product quality and operational efficiency. Accurate weight measurement systems not only aid in meeting regulatory standar...
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Artificial intelligence (AI) models are increasingly finding applications in the field of medicine. Concerns have been raised about the explainability of the decisions that are made by these AI models. In this article...
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