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93 results for “Optimal Networks”
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Research ArticleOpen accessIn the abstractSafety Message Power Transmission Control for Vehicular Ad hoc NetworksGhassan Samara, Sureswaran Ramadas, Wafaa A.H. Al-SalihyProblem statement: Vehicular Ad hoc Networks (VANET) is one of the most challenging research area in the field of Mobile Ad Hoc Networks. Approach: In this research we proposed a dynamic power adjustment protocol that will be used for sending the periodical safety message. (Beacon) based on the analysis of the channel status depending on the channel congestion and the … …Journal of Computer Science, Vol. 6, Issue 10 · 30 Jul 2010 · 7,470 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 · 7,283 accessesView PDFCite
Research ArticleOpen accessIn the abstractNew Constructive Neural Network Architecture for Pattern ClassificationS. S. Sridhar, M. PonnavaikkoProblem statement: Constructive neural network learning algorithms provide optimal ways to determine the architecture of a multi layer perceptron network along with learning algorithms for determining appropriate weights for pattern classification problems. These algorithms initially start with small network and dynamically allow the network to grow by adding and training neurons as needed until a satisfactory solution is found. The … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,570 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrated Metric-Ad Hoc On-Demand Distance Vector: A Routing Protocol over Wireless Mesh NetworksMd. Arafatur Rahman, Farhat Anwar, Md. Saiful AzadProblem statement: Wireless Mesh Networks (WMNs) is an emerging technology for wireless environment. Since WMNs are permanent or semi-permanent network, an efficient and reliable path establishment is the core concern for such type of networks. Several performance metrics has been designed for WMNs such as Expected Transmission Count (ETX), Expected Transmission Time (ETT), interference Aware Routing Metric (iAWARE), Link Type … …Journal of Computer Science, Vol. 5, Issue 7 · 31 Jul 2009 · 7,498 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Use of Taguchi Method to Determine Factors Affecting the Performance of Destination Sequence Distance Vector Routing Protocol in Mobile Ad Hoc NetworksHazura. Mohamed, Muhammad Hisyam Lee, Mazalan Sarahintu et al.In this study, Taguchi method was used to identify the several factors that may affect the performance of Destination Sequence Distance Vector (DSDV) routing protocol. The performance of DSDV routing protocol in mobile ad hoc networks were greatly influence by factors such as node speed, node pause time and traffic load. Problem statement: By using orthogonal experimental design and analysis … …Journal of Mathematics and Statistics, Vol. 4, Issue 4 · 31 Dec 2008 · 7,803 accessesView PDFCite
Research ArticleOpen accessIn the abstractFramework of Regression-Based Graph Matrix Analysis Approach in Multi-Relational Social Network ProblemFord Lumban Gaol, Belawati WidjajaCommunity mining is one of the major directions in social network analysis. Social network analysis has attracted much attention in recent years. Most of the existing methods on community mining assume that there is only one kind of relation in the network and moreover, the mining results are independent of the users’ needs or preferences. However, in reality, there exist … …Journal of Mathematics and Statistics, Vol. 4, Issue 1 · 31 Mar 2008 · 6,927 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Networks for Interferences Suppression in DS/CDMA with Rayleigh Fading Channel and Power Control ErrorY. Jabrane, R. Iqdour, B. Ait Essaid et al.The exponential chip weighting waveforms have been designed with the purpose of multiple access interferences (MAI) rejection based on the concept that the optimum despreading sequence in reference emphasizes the transitions in the received spreading signal of interest. The despreading sequence weighted by exponential chip waveforms was determined by only one parameter. The objective of this study, was to introduce … …Journal of Computer Science, Vol. 3, Issue 3 · 31 Mar 2007 · 6,387 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzy Automata Induction using Construction MethodMo Z. Wen, Wan MinRecurrent neural networks have recently been demonstrated to have the ability to learn simple grammars. In particular, networks using second-order units have been successfully at this task. However, it is often difficult to predict the optimal neural network size to induce an unknown automaton from examples. Instead of just adjusting the weights in a network of fixed topology, we adopt … …Journal of Mathematics and Statistics, Vol. 2, Issue 2 · 30 Jun 2006 · 7,213 accessesView PDFCite
Research ArticleOpen accessIn the abstractChilled Water VAV System Optimization and Modeling Using Artificial Neural NetworksRand Talib, Nabil Nassif, Maya Arida, Taher Abu-Lebdehin 2016, It was estimated that about 40% of total U.S. energy consumption was consumed by the residential and commercial sectors. According to EIA, in 2009, the energy consumption in U.S. homes was 48% which was down from 58% in 1993 Residential Energy Consumption Survey (RECS). The development of building energy savings methods and models becomes apparently more necessary for … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 4 · 23 Oct 2018 · 7,470 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrated Machine Learning Model for Heart Disease Classification and CategorizationSrikanth Meda, Raveendrababu BhogapathiProgressions in the coordination among the machine learning algorithms, helped to achieve high accuracy and reliability in decision-making systems. Due to the impact and importance of heart diseases in real life, designing the efficient heart disease prediction model become a pivotal aspect today. Former research scholars applied the popular supervised machine learning models like Decision Trees, Naïve Bayes, ANN's, and … …Journal of Computer Science, Vol. 18, Issue 4 · 19 Apr 2022 · 6,539 accessesView PDFCite