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Research ArticleOpen accessIn the keywordsForecasting Peak Load Electricity Demand Using Statistics and Rule Based ApproachZ. Ismail, A. Yahya, K. A. MahpolProblem statement: Forecasting of electricity load demand is an essential activity and an important function in power system planning and development. It is a prerequisite to power system expansion planning as the world of electricity is dominated by substantial lead times between decision making and its implementation. The importance of demand forecasting needs to be emphasized at all level as … …American Journal of Applied Sciences, Vol. 6, Issue 8 · 31 Aug 2009 · 7,936 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting Gold Prices Using Multiple Linear Regression MethodZ. Ismail, A. Yahya, A. ShabriProblem statement: Forecasting is a function in management to assist decision making. It is also described as the process of estimation in unknown future situations. In a more general term it is commonly known as prediction which refers to estimation of time series or longitudinal type data. Gold is a precious yellow commodity once used as money. It was made … …American Journal of Applied Sciences, Vol. 6, Issue 8 · 31 Aug 2009 · 11,091 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Efficient Implementation of Re-Sampling Technique for High Performance Multiple Classifier SystemsS. Sathiyabama, K. Thyagarajah, D. AyyamuthukumarDue to the large size of the database, the entire training dataset could not be used to construct the classifiers. One popular solution is to separate stream data into chunks, learn a base classifier from each chunk and then integrate all base classifiers to form Multiple classifier system (MCS). Sometimes this data streams does not include all the classes in … …Journal of Computer Science, Vol. 3, Issue 4 · 30 Apr 2007 · 7,014 accessesView PDFCite
Research ArticleOpen accessIn the keywordsModelling the Error Term of Australia Gross Domestic ProductAyodele Abraham Agboluaje, Suzilah Ismail, Chee Yin YipThe main aim of this study is to model the Gross Domestic Product (GDP) with the new Combine White Noise (CWN) Model and compare the results with the Vector Autoregressive (VAR) Model and Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) Model which are the existing models. The CWN model estimation yields best results with least information criteria and high log likelihood … …Journal of Mathematics and Statistics, Vol. 12, Issue 4 · 2 Nov 2016 · 6,930 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comparison of Explicit Semi-Analytical Numerical Integration Methods for Solving Stiff ODE SystemsE.R. El-Zahar, H.M. Habib, M.M. Rashidi, I.M. El-DesokyIn this study, a comparison among three semi-analytical numerical integration algorithms for solving stiff ODE systems is presented. The algorithms are based on Differential Transform Method (DTM) which are Multiple-Step DTM (MsDTM), Enhanced MsDTM (E-MsDTM) and MsDTM with Padé approximants (MsDTM-P). These methods can be classified as explicit one step semi-analytical numerical integration methods. The error and stability analysis of … …American Journal of Applied Sciences, Vol. 12, Issue 5 · 26 Jun 2015 · 6,955 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Hybrid Method for Automatic Speech Recognition Performance Improvement in Real World Noisy EnvironmentUrmila Shrawankar, Vilas ThakareIt is a well known fact that, speech recognition systems perform well when the system is used in conditions similar to the one used to train the acoustic models. However, mismatches degrade the performance. In adverse environment, it is very difficult to predict the category of noise in advance in case of real world environmental noise and difficult to achieve … …Journal of Computer Science, Vol. 9, Issue 1 · 27 Feb 2013 · 7,754 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDesign of an Error Tolerant AdderA. N. Jayanthi, C. S. RavichandranProblem statement: In modern VLSI technology, the occurrence of all kinds of errors has become inevitable. By adopting an emerging concept in VLSI design and test, Error Tolerance (ET), a novel Error-Tolerant Adder (ETA) is proposed. The ETA is able to ease the strict restriction on accuracy and at the same time achieve tremendous improvements in both the power consumption … …American Journal of Applied Sciences, Vol. 9, Issue 6 · 13 Mar 2012 · 7,249 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFuzzy Time Series: An Application to Tourism Demand ForecastingMuhammad Hisyam Lee, Maria Elena Nor, Suhartono et al.Problem statement: Forecasting is very important in many types of organizations since predictions of future events must be incorporated into the decision-making process. In the case of tourism demand, better forecast would help directors and investors make operational, tactical and strategic decisions. Besides that, government bodies need accurate tourism demand forecasts to plan required tourism infrastructures, such as accommodation site … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 8,474 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Gene Selection Algorithm using Bayesian Classification ApproachAlok Sharma, Kuldip K. PaliwalIn this study, we propose a new feature (or gene) selection algorithm using Bayes classification approach. The algorithm can find gene subset crucial for cancer classification problem. Problem statement: Gene identification plays important role in human cancer classification problem. Several feature selection algorithms have been proposed for analyzing and understanding influential genes using gene expression profiles. Approach: The feature selection … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 8,307 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Improved Face Recognition Technique Based on Modular LPCA ApproachMathu Soothana S. Kumar, Retna Swami, Muneeswaran KaruppiahProblem statement: A face identification algorithm based on modular localized variation by Eigen Subspace technique, also called modular localized principal component analysis, is presented in this study. Approach: The face imagery was partitioned into smaller sub-divisions from a predefined neighborhood and they were ultimately fused to acquire many sets of features. Since a few of the normal facial features of … …Journal of Computer Science, Vol. 7, Issue 12 · 22 Oct 2011 · 6,950 accessesView PDFCite