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14 articles for “Radial Basis Functions”
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The Comparison in Time Series Forecasting of Air Traffic Data by Autoregressive Integrated Moving Average Model, Radial Basis Function and Elman Recurrent Neural Networks
Abstract: Nowadays, nonlinear time series and artificial neural networks (ANN) models are used for forecasting in the field of business, agriculture and soon. Recent studies have shown, ANN have been successfully used for forecasting of financial and agriculture data series The classical methods used for time series prediction like Box-Jenkins or ARIMA assumes that there is a linear relationship between inputs and outputs. ANN have more advantages that can approximate to …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 3, 2018 · pp. 75–90 Read article
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Application of Radial Basis Function Neural Network in Power Quality Events Classification
Abstract: Power Quality concerns have become more important as the Smart Grid has evolved. Computers, microprocessor-controlled electronic loads, and power electronic devices are all used in urban development. Disturbances in power quality are caused by these electronic devices. Variations in the amplitude and frequency of system voltages and currents from their nominal levels identify PQ difficulties. We offer a hybrid technique to accomplishing this goal in this paper. To classify PQ …
Published in Trends in Electrical Engineering · Vol. 12, Issue 1, 2022 · pp. 20–40 Read article
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Designing of Low Pass Finite Impulse Response Filter using Radial Basis Function Neural Network
Abstract: The present paper investigates an approach to design and analysis of a low pass finite impulse response (FIR) filter using artificial neural network. The main aim of design is to find out the filter coefficients that define the filter transfer functions. A datasheet of 40 different values of h (n), i.e., coefficient of digital low pass FIR filter are used for filter designing. In this paper Radial Basis Function method …
Published in Journal of Control & Instrumentation · Vol. 5, Issue 2, 2014 · pp. 21–24 Read article
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Radial Basis Function Neural Networks for Rainfall-Runoff Modeling
Abstract: Rainfall-runoff process is purely nonlinear and varies spatially as well as temporally. Any hydrological model requires many parameters which represent different components of the process. Availability of all the parameters is difficult for any catchment and probabilistic generation of such type of data is impossible. Under such circumstances, artificial neural networks (ANNs) have proven to be a better tool to model the rainfall-runoff process with minimum available data. The present …
Published in Journal of Water Resource Engineering and Management · Vol. 1, Issue 2, 2014 · pp. 11–18 Read article
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Geospatial Depiction of Groundwater Level Disparities on a Temporal Component over Portions of Cuddapah District, India Using Contemporary Geo Tools and Interrelated Statistics
Abstract: This paper mainly focuses on comparing methods such as Deterministic methods, Geostatistical methods and Interpolation methods in order to obtain a good fit to represent groundwater level disparities existed in the study area from 1996 to 2015. Inverse Distance Weighting, Global Polynomial Interpolation, Radial Basis Functions, Local Polynomial Interpolation, Kriging, Empirical Bayesian Kriging, Kernel smoothing and Diffusion Kernel were the methods tested for the present study. The data set procured …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 6, Issue 2, 2017 · pp. 13–29 Read article
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Voice Recognition Technique Using Neural Network
Abstract: The scope of voice recognition ranges from access control to forensics. In a given environment the system will be able to recognize the correct speaker. This voice recognition technology can also recognize the voice based on their gender. This system uses the basic idea of Artificial Neural Network (ANN). Various techniques of ANN have been used in past to implement this system. This paper gives us some of the important …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 2, Issue 1, 2015 · pp. 15–18 Read article
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Integral Sliding Mode Control: A Review of Applications
Abstract: Integral Sliding Mode Control (ISMC) has emerged as a robust and efficient method for handling nonlinear systems with uncertainty, turbulence and external disturbances. This study provides a detailed review of ISMC and its design foundations, design methods, practical application aspects and recent developments are included. ISMC design methodology is explored, to be extended with various design methods with different design methods. Recent advances in research, chatter reduction techniques, applications in …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 1, 2024 · pp. 25–35 Read article
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A Neural Network Approach to Study the Bandwidth of C-Shaped Microstrip Antenna
Abstract: This paper presents the use of artificial neural network for the estimation of frequency band and bandwidth of a line feed C-Shaped Microstrip patch antenna. The results obtained by using ANNs are compared with IE3D simulation and found quite satisfactory. The designed antenna operates in the frequency range (1.735 to 1.945 GHz). The antenna is designed using glass epoxy between the ground plane and patch and simulated on the Zeland …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 2, Issue 3, 2015 · pp. 24–30 Read article
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Unsupervised Learning Techniques in Neural Network for Face Recognition
Abstract: This paper represents the review of systematic comparison between of unsupervised learning algorithms for face recognition. In neural network, different algorithms are used for face recognition. Each algorithm has different accuracy factors. Commonly these methods asset a set of base images and serve faces as linear combo of images. In our proposed review, firstly we discuss about the face detection using neural network along with the concept of digital image …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 1, 2020 · pp. 25–29 Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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Selection of Cluster Head in Wireless Sensor Network towards Extending Network Life Time
Abstract: Reduced energy consumption and extended lifetime are basic requirements of Wireless Sensor Network (WSN) with distributed nature and dynamic topological changes. The motes are arranged in clusters and only one mote is chosen as cluster head to synchronize and data routing. The proposed work introduces an innovative approach of choosing cluster head in artificially intelligent wireless sensor network. In the proposed work, the residual energy consumption plays the major role …
Published in Journal of Microcontroller Engineering and Applications · Vol. 3, Issue 3, 2016 · pp. 1–10 Read article
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Comparative Analysis of Artificial Intelligence-based MPPT Algorithms for Wind Energy System
Abstract: By extracting maximum possible power from a wind generator system, the efficiency of the system can be increased. Radial basis function (RBF), feed forward back propagation (FFBP) and adaptive neuro-fuzzy inference system (ANFIS) are recognized as the universal estimators. This paper presents a single network based maximum power point tracking (MPPT) of a wind turbine system using these algorithms. The single network based maximum power extraction method is simple and …
Published in Journal of Power Electronics and Power Systems · Vol. 10, Issue 3, 2020 · pp. 7–18 Read article
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Automated Thyroid Nodule Detection in Ultrasound Image using Optimal Neural Network Classifier
Abstract: Malignant thyroid nodule detection is an important issue in thyroid ultrasonography image processing. Literature reports many algorithms in this domain. This research aims to design optimal decision support system (DSS) for ultrasound thyroid nodule image characterization into benign and malignant classes. Thyroid nodule region is segmented to extract texture features from thyroid nodule ultrasound images acquired from 38 patients using gray level co-occurrence matrix (GLCM) and statistical properties. These features …
Published in Journal of Advancements in Robotics · Vol. 2, Issue 2, 2015 · pp. 15–25 Read article
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Bangla Handwritten Digit and Basic Letter Recognition Using Machine Learning Techniques
Abstract: AbstractThe usage of computer is increasing day by day in Bangladesh, so the use of Bangla is increasing in computer. Furthermore, the use of Bangla handwritten character is also increasing in many computer applications. There exist many techniques for recognition of handwritten character. From the studies we see that machine learning techniques are better techniques for recognition of handwritten character than others. A necessary prerequisite for measuring the performance of …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 3, 2016 · pp. 1–15 Read article