In this work, using Modular Differential Evolution (Modular DE), we investigate the impact of parameter memory size (MS) on the search performance of Success-history based parameter adaptation (L-SHADE) for Differenti...
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This paper analyzes the shortest path problem (SPP) in social networks, based on the investigation and implementation of different methods on a simulated example. The objectives of the paper include identification of ...
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The heightened transmissibility of the coronavirus presents significant hazards for medical professionals conducting face-to-face COVID-19 swab tests. To address this concern, we recommend employing a 4-axis instructi...
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The certification of safety properties and interpretation of neural networks is a topic of great concern. We recently devised an automata-based approach for addressing these tasks. It translates a neural network with ...
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The immune system goes through a profound transformation during pregnancy,and certain unexpected maternal complications have been correlated to this *** ability to correctly examine,diagnoses,and predict pregnancy-has...
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The immune system goes through a profound transformation during pregnancy,and certain unexpected maternal complications have been correlated to this *** ability to correctly examine,diagnoses,and predict pregnancy-hastened diseases via the available big data is a delicate problem since the range of information continuously increases and is *** approaches for disease diagnosis/classification have been established with the use of data mining ***,such methods do not provide an appropriate classification/diagnosis ***,single learning approaches are used to create the bulk of these *** issues may be made more accurate by combining predictions from many different *** a result,we used the Ensembling of Neuro-Fuzzy(E-NF)method to perform a high-level classification of medical diseases.E-NF is a layered computational model with self-learning and self-adaptive capabilities to deal with specific problems,such as the handling of imprecise and ambiguous data that may lead to uncertainty concerns that specifically emerge during the classification *** data,Training phase,Ensemble phase,and Testing phase make up the complete procedure for the suggested *** preprocessing includes feature extraction and dimensionality *** such processes,the training phase includes the fuzzification process of medical ***,training of input data was done using four types of NF techniques:Fuzzy Adaptive Learning Control Network(FALCON),Adaptive Network-based Fuzzy Inference System(ANFIS),Self Constructing Neural Fuzzy Inference Network(SONFIN)and/Evolving Fuzzy Neural Network(EFuNN).Later,in the ensemble phase,all the NF methods’predicted outcomes are integrated,and finally,the test results are evaluated in the testing *** outcomes indicate that the method could predict impaired glucose tolerance,preeclampsia,gestational hypertensive abnormalities,bacteriuria,and iron deficien
American Sign Language (ASL) recognition aims to recognize hand gestures, and it is a crucial solution to communicating between the deaf community and hearing people. However, existing sign language recognition algori...
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A common practice in software development is to include linters, static analysis tools that warn developers about potential issues in the code, in the software quality assurance process. Actionable warnings generated ...
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In light of this unmistakable exponential data expansion, visual media archiving must be rethought. Human generated meta-data might not be sufficient for efficient data retrieval. Object detection and object recogniti...
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Prior study has developed the RouteSegmentation algorithm to identify the perimeter area surrounding a route. In this study, a comparative experiment was carried out to investigate the performance of the RouteSegmenta...
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The increased quality and human-likeness of AI generated texts has resulted in a rising demand for neural text detectors, i.e. software that is able to detect whether a text was written by a human or generated by an A...
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