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200 results for “artificial neural network”
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Research ArticleOpen accessIn the keywordsCharacterization of the Changes in Opened Sufu Bottles During Storage with Mathematical ModelJingJing Liang, Dawei Li, Ruiqin Shi et al.Artificial Neural Network (ANN) is a type of nonlinear empirical model, which can clarify the complex relation between the inputs and outputs that allows it to approximate any nonlinear function for making predictions. The objective of this study is to monitor the Biogenic Amines (BAs) content and selected physicochemical properties of sufu (a traditional Chinese fermented soybean product) along time. … …American Journal of Biochemistry and Biotechnology, Vol. 14, Issue 4 · 12 Dec 2018 · 9,357 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Methodology for Neural Network Training Ensures Error Reduction in Time Series ForecastingPaola A. Sánchez-Sánchez, José Rafael García-GonzálezArtificial Neural Networks (ANN) consists of some components, such as architecture and learning algorithm. These components have a significant effect on the performance of the ANN, but finding good parameters is a difficult task to achieve. An important requirement for this task is to ensure the reduction of error when inputs and/or hidden neurons are added. In practice, it is … …Journal of Computer Science, Vol. 13, Issue 7 · 4 Jul 2017 · 7,178 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comparison between Different Data Mining Algorithms in Freight Mode ChoiceAmir Samimi, Hesamoddin Razi-Ardakani, Amir NohekhanThis research aims to study application of support vector machine algorithm, artificial neural networks and five different types of decision trees in predicting mode choice of freight transportation. Performance of these models has been compared with log it model which is one the most prevalent statistical models in the field. Effect of factors such as cargo weight, distance, type and … …American Journal of Applied Sciences, Vol. 14, Issue 2 · 5 Feb 2017 · 7,626 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHydrological Forecasting Using Hybrid Data-Driven ApproachYoungmin Seo, Sungwon KimThis study develops a hybrid model, EEMD-FANN, coupling feed Forward Artificial Neural Network (FANN) and Ensemble Empirical Mode Decomposition (EEMD) for improving the accuracy of daily river stage forecasting. An original river stage data is broken down into a residue and Intrinsic Mode Functions (IMFs) using the EEMD and different FANNs are developed as forecasting models for the decomposed IMFs … …American Journal of Applied Sciences, Vol. 13, Issue 8 · 2 Sep 2016 · 8,140 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEvaluation of Interregional Freight Generation Modelling Methods by using Nationwide Commodity Flow Survey DataWirach HirunA trip generation model is one of the four parts of the classical transport planning model, which explores the volume of trip or freight at the originating and destination points of a traffic analysis zone. The process of calibrating a trip generation model needs appropriate data. Freight transport data are always robust and a powerful calibration technique is required to … …American Journal of Engineering and Applied Sciences, Vol. 9, Issue 3 · 18 Aug 2016 · 8,113 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSLOPE STABILITY ANALYSIS OF KALLAR-COONOOR HILL ROAD STRETCH OF THE NILGIRISP. Nalina, T. Meenambal, R. Sathyanarayan SridharThe stability of slopes is always under severe threats in many parts of Western Ghats, especially in Kallar-Coonoor hill road stretch, causing disruption, loss of human life and economy. To minimize the instability of soil slope in between Kallar-Coonoor, a critical evaluation of roads is required. The stability of slopes depends on the soil shear strength parameters such as Cohesion, … …Journal of Computer Science, Vol. 10, Issue 7 · 4 Feb 2014 · 7,406 accessesView PDFCite
Research ArticleOpen accessIn the keywordsGENERALIZED REGRESSION NEURAL NETWORK BASED EXPERT SYSTEM FOR HEPATITIS B DIAGNOSISC. Mahesh, E. Kannan, M. S. SaravananHepatitis B is a potentially life-threatening liver infection caused by the hepatitis B virus. The virus interferes with the function of the liver while replicating in hepatocytes. It is a major global health problem and the most serious type of viral hepatitis. Chronic liver disease is caused by viral hepatitis and putting people at high risk of death from cirrhosis … …Journal of Computer Science, Vol. 10, Issue 4 · 3 Dec 2013 · 6,985 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA REVIEW ON THE DEVELOPMENT OF INDONESIAN SIGN LANGUAGE RECOGNITION SYSTEMSutarman, Mazlina Abdul Majid, Jasni Mohamad ZainSign language is mainly employed by hearing-impaired people to communicate with each other. However, communication with normal people is a major handicap for them since normal people do not understand their sign language. Sign language recognition is needed for realizing a human oriented interactive system that can perform an interaction like normal communication. Sign language recognition basically uses two approaches: … …Journal of Computer Science, Vol. 9, Issue 11 · 27 Sep 2013 · 8,698 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHybrid of Fuzzy Clustering Neural Network Over NSL Dataset for Intrusion Detection SystemDahlia Asyiqin Ahmad Zainaddin, Zurina Mohd HanapiIntrusion Detection System (IDS) is one of the component that take part in the system defence, to identify abnormal activities happening in the computer system. Nowadays, IDS facing composite demands to defeat modern attack activities from damaging the computer systems. Anomaly-Based IDS examines ongoing traffic, activity, transactions and behavior in order to identify intrusions by detecting anomalies. These technique identifies … …Journal of Computer Science, Vol. 9, Issue 3 · 4 May 2013 · 6,579 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Overview of Research Challenges for Classification of Cardiotocogram DataC. Sundar, M. Chitradevi, G. GeetharamaniCardiotocography (CTG) is a simultaneous recording of Fetal Heart Rate (FHR) and Uterine Contractions (UC). The most common diagnostic techniques to evaluate maternal and fetal well-being during pregnancy and before delivery. By observing the Cardiotocography trace patterns doctors can understand the state of the fetus. There are several signal processing and computer programming based techniques for interpreting a typical Cardiotocography … …Journal of Computer Science, Vol. 9, Issue 2 · 2 Apr 2013 · 7,835 accessesView PDFCite