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Research ArticleOpen accessIn the abstractPredicting Support and Resistance Indicators for Stock Market with Fibonacci Sequence in Long Short-Term MemoryThambusamy Velmurugan, Thiruvalluvan IndhumathyPredictive data analytics is a branch of data analytics where models are designed that effectively interpret; anticipate outcomes by analyzing present data to make predictions about future. One of the major attributes for prediction is time and there have been a considerable number of time series analytical models that are used for forecasting. Long Short-Term Memory (LSTM) is a deep … …Journal of Computer Science, Vol. 16, Issue 10 · 28 Oct 2020 · 7,316 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Acceptance Criterion (AAC) Algorithm for Optimization ProblemsAnmar AbuhamdahOptimization methods commonly are designed for solving the optimization problems. Local search algorithms are optimization method, which are good candidate in exploiting the search space. However, most of them need parameter tuning and incapable of escaping from local optima. This work proposes non-parametric Acceptance Criterion (AC) that not relies on user-defined, which motivate to propose an Adaptive Acceptance Criterion (AAC). … …Journal of Computer Science, Vol. 11, Issue 4 · 23 Jul 2015 · 6,969 accessesView PDFCite
Research ArticleOpen accessIn the abstractArabic Named Entity Recognition Using Artificial Neural NetworkNaji F. Mohammed, Nazlia OmarProblem statement: Named Entity Recognition (NER) is a task to identify proper names as well as temporal and numeric expressions, in an open-domain text. The NER task can help to improve the performance of various Natural Language Processing (NLP) applications such as Information Extraction (IE), Information Retrieval (IR) and Question Answering (QA) tasks. This study discusses on the Named Entity … …Journal of Computer Science, Vol. 8, Issue 8 · 16 Jul 2012 · 8,676 accessesView PDFCite
Research ArticleOpen accessIn the abstractDecision Based Development of Productline: A Quintessence Usability ApproachR.V. Siva Balan, M. PunithavalliProblem statement: A well designed user interface is comprehensible and controllable, helping users to complete their work successfully and efficiently and to feel competent and satisfied. To improve the usability of a software system, usability patterns can be applied. However, there are short comes shows that the software architecture of a system restricts certain usability patterns from being modified after … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 6,880 accessesView PDFCite
Research ArticleOpen accessIn the abstractNasal Administration of Quercetin Liposomes Modulate Cognitive Impairment and Inhibit Acetylcholinesterase Activity in HippocampusTerdthai Tong-Un, Supaporn Muchimapura, Wathita Phachonpai, Jintanaporn WattanathornProblem statement: Oxidative stress is a major factor implicated in the degeneration of cholinergic neurons in Alzheimer’s Disease (AD). Several reports have indicated that antioxidant intake is beneficial to delay or inhibit the progression of this disease. Presently, Acetylcholinesterase (AChE) inhibitors are the mainstay of therapy for AD. Quercetin, one of the flavonoids in fruits and vegetables, has a powerful … …Neuroscience International, Vol. 1, Issue 1 · 30 Jun 2010 · 7,170 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimal Thyristor Control Series Capacitor Neuro-Controller for Damping OscillationsM. Magaji, M. W. MustafaThis study applies a neural-network-based optimal TCSC controller for damping oscillations. Optimal neural network controller is related to model-reference adaptive control, the network controller is developed based on the recursive "pseudo-linear regression". Problem statement: The optimal NN controller is designed to damp out the low frequency local and inter-area oscillations of the large power system. Approach: Two multilayer-perceptron neural networks … …Journal of Computer Science, Vol. 5, Issue 12 · 31 Dec 2009 · 7,281 accessesView PDFCite
Research ArticleOpen accessIn the abstractChange Detection Using Neural Network with Improvement Factor in Satellite ImagesM. A. Fkirin, S. M. Badwai, Sayed A. MohamedProblem statement: The aim of this study is to investigate the applicability of using the neural network techniques in change detection of remotely sensed data. Approach: In addition, the tuning parameters of the network, such as encoding the output classes, adding the momentum term and learning rate, are investigated in order to achieve best network performance. Results: Neural network-based change … …American Journal of Environmental Sciences, Vol. 5, Issue 6 · 31 Dec 2009 · 6,648 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Arabic Text-To-Speech System Based on Artificial Neural NetworksGhadeer Al-Said, Moussa AbdallahProblem statement: With the rapid advancement in information technology and communications, computer systems increasingly offer the users the opportunity to interact with information through speech. The interest in speech synthesis and in building voices is increasing. Worldwide, speech synthesizers have been developed for many popular languages English, Spanish and French and many researches and developments have been applied to those … …Journal of Computer Science, Vol. 5, Issue 3 · 31 Mar 2009 · 7,368 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenetic Algorithm Based Probabilistic Motif Discovery in Unaligned Biological SequencesM. Hemalatha, K. VivekanandanFinding motif in biosequences is the most important primitive operation in computational biology. There are many computational requirements for a motif discovery algorithm such as computer memory space requirement and computational complexity. To overcome the complexity of motif discovery, we propose an alternative solution integrating genetic algorithm and Fuzzy Art machine learning approaches for eliminating multiple sequence alignment process. Problem … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,729 accessesView PDFCite