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Research ArticleOpen accessPhrase in the titleFUZZY MODEL OPTIMIZATION FOR TIME SERIES DATA USING A TRANSLATION IN THE EXTENT OF MEAN ERRORNurhayadi, Subanar, Abdurakhman, Agus Maman AbadiRecently, many researchers in the field of writing about the prediction of stock price forecasting, electricity load demand and academic enrollment using fuzzy methods. However, in general, modeling does not consider the model position to actual data yet where it means that error is not been handled optimally. The error that is not managed well can reduce the accuracy of … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 2 Jun 2014 · 6,733 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Comparative Performance Analysis of Multiple-Input Multiple-Output using MATLAB with Zero Forcing and Minimum Mean Square Error EqualizersBara'u Gafai Najashi, Tan XiaohengProblem statement: Multiple-Input Multiple-Output systems (MIMO) were regarded as one of the most promising technologies in field of wireless communication. Generally considered as one of the several forms of smart antenna technology, it offers considerable increase in data throughput and link range without additional bandwidth or transmit power. The general idea involves the use of several antennas at the transmitter … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 3 · 29 Nov 2011 · 8,298 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Novel Channel Estimation Technique for Complexity Reduction of Least Minimum Mean Square ErrorHany Mohamed El-Ansary, Hussein Ghouz, Ashraf Mamdouh Aziz, Gamal MabroukChannel estimation technique is to predict the frequency response of the radio channel using pilot signal. Channel estimation technique is important part of LTE receiver design. Such technique is used to recover the transmitted signal correctly and to know how the channel conditions are changed over frequency and time. Each channel estimator has a specified complexity computed according to its … …American Journal of Applied Sciences, Vol. 10, Issue 10 · 5 Sep 2013 · 6,999 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSpeech Enhancement Using Minimum Mean-Square Error Amplitude Estimators Under Normal and Generalized Gamma DistributionChabane Boubakir, Daoud BerkaniProblem statement: In this study, DFT-based speech enhancement via Minimum Mean-Square Error (MMSE) amplitude estimators was considered. Approach: Several variants of the basic approach (MMSE-STSA) have been proposed over the years to address certain shortcomings, chiefly the quality of the remnant noise and its trade-off with speech distortion. In this study, we presented a comparative study between the MMLSA and … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,106 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBayesian Estimation for Lomax Distribution: A Comparison of Loss Functions Using Jeffreys PriorsHuda Mohammed AlomariThis study investigates the estimation of the shape parameter for the Lomax distribution using complete data. We compare the performance of the classical Maximum Likelihood Estimation (MLE) method against the Bayesian framework. Within the Bayesian approach, three distinct loss functions were utilized: the linear exponential (LINEX), general entropy, and weighted general entropy loss functions. The precision of these estimators was … …Journal of Mathematics and Statistics, Vol. 21, Issue 1 · 24 Dec 2025 · 2,635 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFuel Prediction Model for Driving Patterns Using Machine Learning TechniquesManjunath TK, Ashok Kumar PSIn recent years, the demand for fuel efficiency has become a crucial aspect of the automotive industry. Predicting fuel economy accurately is essential for optimizing vehicle performance and reducing environmental impact. This proposed model presents a machine learning-based approach for developing a fuel prediction model using the real dataset. The model aims to predict fuel efficiency for different drivers by … …Journal of Computer Science, Vol. 20, Issue 3 · 29 Jan 2024 · 5,480 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPredicting 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 keywordsWeather Forecasting Using Merged Long Short-Term Memory Model (LSTM) and Autoregressive Integrated Moving Average (ARIMA) ModelAfan Galih Salman, Yaya Heryadi, Edi Abdurahman, Wayan SupartaWeather forecasting is an interesting research problem in flight navigation area. One of the important weather data in aviation is visibility. Visibility is an important factor in all phases of flight, especially when the aircraft is maneuvering on or close to the ground, i.e., during taxi-out, take-off and initial climb, approach and landing and taxi-in. The aim of these study … …Journal of Computer Science, Vol. 14, Issue 7 · 28 Jun 2018 · 11,422 accessesView PDFCite
Research ArticleOpen accessIn the keywordsVideo Coding Technique Using 3D Dualtree Discrete Wavelet Transform with Multi Objective Particle Swarm Optimization ApproachesThamarai Muthusamy, Shanmugalakshmi RamachandranWavelet-based image compression with Wavelet transform based motion compensated video codec performs better compression to meet the rate and distortion constraints in video transmission with the available bandwidth than the block based techniques. However, it is well known that the 2D DWT does not represent directional features of images efficiently. Lots of efforts have been contributed to multiscale directional representation. … …American Journal of Applied Sciences, Vol. 10, Issue 2 · 20 Feb 2013 · 6,591 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFetal Electrocardiogram Extraction Using Let TechniquesS. Hemajothi, K. Helen PrabhaFetal Electrocardiogram Extraction (FECG) identifies the congenital heart problems at the earlier stage. The major problem in the non invasive procedure is the extraction of FECG from Maternal ECG (MECG) and many interferences. The proposed methods (i) Combination of Adaptive Neuro Fuzzy Inference (ANFIS) and Fractional spline wavelet (ii) Combination of Fractional spline wavelet and ANFIS (iii) Combination of ANFIS … …Journal of Computer Science, Vol. 8, Issue 9 · 16 Aug 2012 · 7,311 accessesView PDFCite