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68 articles for “training problems”
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Research ArticleOpen accessIn the abstractAnalyzing Effect on Residual Learning by Gradual Narrowing Fully-Connected Layer Width and Implementing Inception Block in Convolution LayerSaurabh SharmaResearch conducted on the advancement of CNN architecture for computer vision problems focuses on strategically choosing and modifying convolution hyperparameters (kernel, pooling, etc.). However, these research works don't exploit the advantage of employing multi fully-connected layers post the core schema to avail further performance improvements, which have been identified as the first research gap. Studies were also conducted to address … …Journal of Computer Science, Vol. 18, Issue 5 · 24 May 2022 · 6,051 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Evolving Autoregressive Predictor for Time Series ForecastingDe Z. Li, Wilson Wang, Fathy IsmailAutoregressive (AR) model is a common predictor that has been extensively used for time series forecasting. Many training methods can used to update AR model parameters, for instance, least square estimate and maximum likelihood estimate; however, both techniques are sensitive to noisy samples and outliers. To deal with the problems, an evolving AR predictor, EAR, is developed in this study … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 1 · 8 Apr 2015 · 6,972 accessesView PDFCite
Research ArticleOpen accessIn the abstractWEEDS IDENTIFICATION USING EVOLUTIONARY ARTIFICIAL INTELLIGENCE ALGORITHMAhmed M. Tobal, Sahar A. MokhtarIn a world reached a population of six billion humans increasingly demand it for food, feed with a water shortage and the decline of agricultural land and the deterioration of the climate needs 1.5 billion hectares of agricultural land and in case of failure to combat pests needs about 4 billion hectares. Weeds represent 34% of the whole pests while … …Journal of Computer Science, Vol. 10, Issue 8 · 4 Mar 2014 · 7,827 accessesView PDFCite
Research ArticleOpen accessIn the abstractSteel Plates Faults Diagnosis with Data Mining ModelsMahmoud Fakhr, Alaa M. ElsayadProblem statement: Over the last two decades, Fault Diagnosis (FD) has a major importance to enhance the quality of manufacturing and to lessen the cost of product testing. Actually, quick and correct FD system helps to keep away from product quality problems and facilitates precautionary maintenance. FD may be considered as a pattern recognition problem. It has been gaining more … …Journal of Computer Science, Vol. 8, Issue 4 · 31 Jan 2012 · 11,383 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Review Study on Spiritual Intelligence, Adolescence and Spiritual Intelligence, Factors that may Contribute to Individual Differences in Spiritual Intelligence and the Related TheoriesMaryam Hosseini, Habibah Elias, Steven Eric Krauss, Siti AishahProblem statement: This study reviewed the articles about adolescence, its relation to spiritual intelligence and the related theories. The adolescence period is the best time to develop positive emotions and training skills, because adolescents are seeking to find their identity and their future personality at this period. Approach: Spiritual intelligence had a significant influence on the quality of life and … …Journal of Social Sciences, Vol. 6, Issue 3 · 30 Sep 2010 · 10,377 accessesView PDFCite
Research ArticleOpen accessIn the abstractRule Extraction from Radial Basis Functional Neural Networks by Using Particle Swarm OptimizationM. R. Senapati, I. Vijaya, P. K. DashRadial basis functional neural networks (RBFNN) provide an outstanding possibility for generating rules for solving pattern classification problems. One of the most important factors in RBFNN is finding out the center and spread. This paper examines rules extracted from RBF networks trained by Particle swarm Optimization (PSO). The selection of the RBFNN centers, spreads and the network weights can be … …Journal of Computer Science, Vol. 3, Issue 8 · 31 Aug 2007 · 6,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Classification and Support Vector Machine for Detecting Epilepsyusing Electroencephalograph RecordsHeri Kuswanto, Mutiah Salamah, Muhammad Idrus FachruddinComplexity in data structure has led to the rapid development of computational statistics methods. Machine learning approaches have been introduced and applied to solve complex problems in many fields. This paper applies two common machine learning approaches, Random Forest (RF) and Support Vector Machine (SVM), in the detection of epilepsy. The diagnosis of epilepsy can usually only be made when … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 4 May 2017 · 8,141 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Guideline of using Assistive Technologies and Educational Services for Students with Disabilities in Higher EducationTheeratorn Lersilp, Suchitporn LersilpAssistive Technologies (AT) and Educational Services (ES) are important in the needs of students with disabilities in higher education and their availability should be studied to provide appropriate help for them. The objectives of this study were to explore the problems in using AT and ES for these students and develop a guideline from the perspective of key informants. Data … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 28 Apr 2017 · 7,569 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Modeling Applied to Structured Clinical Data Extracted from Electronic Health Records: An Architectural Hypothesis and A First ExperimentAlessandra Pieroni, Alessandro Cabroni, Francesca Fallucchi, Noemi ScarpatoPredictive analysis is one of current important issues in the healthcare context. A lot of patients’ input data can be obtained from their Electronic Health Records. In our research, we propose a general architecture named Health Prediction Architecture. Initially, we consider that data refer to strongly structured health datasets (no free text). Our objectives are related to exploring some problems … …Journal of Computer Science, Vol. 17, Issue 9 · 7 Sep 2021 · 6,575 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenetic Algorithm for Variable and Samples Selection in Multivariate Calibration ProblemsKelton de Souza Santiago, Anderson Silva Soares, Telma Woerle de Lima et al.One of the main problems of quantitative analytical chemistry is to estimate the concentration of one or more species from the values of certain physicochemical properties of the system of interest. For this it is necessary to construct a calibration model, i.e., to determine the relationship between measured properties and concentrations. The multivariate calibration is one of the most successful … …Journal of Computer Science, Vol. 11, Issue 4 · 8 Jun 2015 · 7,385 accessesView PDFCite