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62 articles for “artificial neural network”
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ANN Based Power Quality Identification and Classification in Wind Solar Hybrid System
Abstract: With the development of new functionalities solar and wind energy based hybrid system are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting is one of the most promising sources. Due to the development of modern power electronics devices the power quality of wind solar hybrid system gets affected. Hence due to the increasing usage of sensitive electronic equipments in wind solar …
Published in International Journal of Electrical Power System and Technology · Vol. 3, Issue 2, 2017 · pp. 6–11 Read article
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Health Care System Analysis Using Different Datasets
Abstract: In this research work, we have discussed data science and various machine learning algorithms like KNN, Support Vector Machine, Artificial neural network, Random forest etc. and the results obtained from these algorithms which can be used for the prediction of heart disease, cancer and in many other fields of medical science. Requirement of data cleaning along with various methods of data cleaning are mentioned here, along with these various issues …
Published in International Journal of Distributed Computing and Technology · Vol. 8, Issue 2, 2022 · pp. 29–37 Read article
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Comparison of Back propagation control algorithm with P-Qtheory for power quality improvement using DSTATCOM under steady state condition
Abstract: Providing consumers with high-quality power is the distribution operator's primary goal. Distribution Static Compensator (DSTATCOM), Dynamic Voltage Restorer (DVR), and Unified Power Quality Conditioner (UPQC) are examples of power converter-based custom power devices (CPDs) that are well-known for enhancing the distribution system's power quality. In order to lessen source-side supply power harmonics, DSTACOM is taken into consideration in this work. Any bespoke power device's performance is heavily dependent on the …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 1, 2026 · pp. 25–34 Read article
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Character Recognition with Neural Network
Abstract: In this project artificial neural network has been called for its application as characters recognizing network. The network is made to learn as per the requirement by training them with some specific patterns that corresponds to the character. The number of input and output layer neurons is chosen. The training patterns and testing patterns are designed using matrices 0’s and 1’s.The weights in the network are adjusted using back propagation …
Published in International Journal of Software Computing and Testing · Vol. 3, Issue 2, 2017 · pp. 32–37 Read article
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A Review of AI and Machine Learning Techniques in Dew Point Pressure Prediction for Gas Condensate Systems
Abstract: Condensate gas reservoirs pose considerable management challenges due to their intricate phase behavior and the critical need for accurate predictions of dew point pressure (PDew). A precise determination of PDew is vital for optimizing production strategies, estimating reserves, and planning enhanced oil recovery operations. Traditional methods for PDew determination often involve experimental analyses that can be both costly and time-consuming, highlighting the necessity for alternative predictive models. This review consolidates …
Published in International Journal of Chemical Engineering and Processing · Vol. 11, Issue 1, 2025 Read article
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SOFT COMPUTING A NEW USE OF SOFT COMPUTING, ARTIFICIAL INTELLIGENCE, FUZZY LOGIC & GENETIC ALGO-RITHM IN BIOINFORMATICS
Abstract: Abstract:Soft registering is make a few dormant in bioinformatics, particularly by producing minimal effort, low exactness (rough), great arrangements. Bioinformatics is an interdisciplinary research zone that is the edge between the natural and computational sciences. Bioinformatics settlement with calculations, databases and data frameworks, web innovations, man-made reasoning and delicate registering, data and calculation hypothesis, basic science, programming building, information mining, picture preparing, demonstrating and recreation, discrete arithmetic, control and framework …
Published in International Journal of Analog Integrated Circuits · Vol. 6, Issue 1, 2020 · pp. 12–26 Read article
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Genre Classification of Music Using Machine Learning
Abstract: One of the most important technological advances of the 21st century is artificial intelligence (AI) and machine learning. They are revolutionizing computers, banking, healthcare, agriculture, music and travel. A strong model has mastered many difficult learning tasks. Speech analysis is one area of artificial intelligence. This includes finding information about music, creating music, and categorizing music. Music data is one of the most complex source data available today. This is …
Published in International Journal of Distributed Computing and Technology · Vol. 8, Issue 2, 2022 · pp. 17–28 Read article
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Evaluation of Machine Learning and Deep Learning Models for Classification Tasks on Crime Data: A Comparative Study
Abstract: The classification of crime data has grown more and more important for public safety and law enforcement due to the increasing demand for precise and effective predictive models. To classify crime data, this study assesses and contrasts the effectiveness of several machine learning (ML) and deep learning (DL) models, such as decision trees, support vector machines, neural networks, and convolutional neural networks. The study evaluates the models' accuracy, efficiency, and …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 1, 2025 · pp. 1–15 Read article
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Neural network based prediction of shear wave velocity for soils
Abstract: The paper presents a study on the prediction of the shear wave velocity (Vs) for all soils using ANN model from cone penetration test data. The input parameters in the obtained of ANN models were vertical effective stress, sleeve friction, cone tip resistance and output was the shear wave velocity. These parameters were considered to construct the ANN model which has 3-2-1 topology in prediction of shear wave velocity. Further, …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 5, Issue 2, 2019 · pp. 23–34 Read article
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Investigation of FSO Communication System Using Various Neural Networks
Abstract: A prospective method for high-speed data transfer via light propagation in free space, such as between buildings, satellites, or metropolitan areas, is Free Space Optics (FSO) communication. FSO systems have great promises, but their performance can be severely hampered by atmospheric disturbances. Problems like fog, rain, and turbulence cause the optical signal to be absorbed and scattered, increasing BER. To address these challenges, various Neural Network (NN) techniques such as …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 12–20 Read article
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AI-Based Noise Reduction Techniques for Digital and Analog Communication Systems
Abstract: Noise is one of the major challenges in modern communication systems because it significantly affects signal quality, transmission efficiency, and overall system reliability. Both digital and analog communication systems are influenced by different types of noise such as thermal noise, impulse noise, quantization noise, atmospheric noise, and channel interference. Conventional noise reduction techniques including filtering, adaptive equalization, and statistical signal processing have been extensively used to improve communication performance. However, …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 1, 2026 · pp. 40–48 Read article
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Prediction of Rainfall Using MLP and RBF Networks for Monsoon and Post-Monsoon Seasons of Pune and Mahabaleshwar Regions
Abstract: Prediction of rainfall for a river basin has utmost importance for planning of irrigation and drainage system as also for command area development. For example, analysis of consecutive days of rainfall is more relevant for drainage design of agricultural lands whereas analysis of weekly rainfall data is relevant for planning of cropping pattern. Likewise, analysis of monthly and seasonal data is more useful for water management practices. With the development …
Published in International Journal of Water Resources Engineering · Vol. 7, Issue 1, 2021 · pp. 34–51 Read article
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Health Monitoring System for Fault Identification on Centrifugal Pump Using ML
Abstract: Centrifugal pumps are crucial equipment widely used in various industries, and their reliable operation is essential for maintaining production and preventing costly downtimes. This paper proposes a comprehensive health monitoring system for centrifugal pumps that combines model-driven and data- driven approaches, leveraging artificial intelligence (AI) and machine learning (ML) techniques. The system incorporates demand prediction using artificial neural networks and fault diagnosis employing different ML classifiers, such as decision trees …
Published in International Journal of Mechanics and Design · Vol. 10, Issue 2, 2024 · pp. 1–12 Read article
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Deep Learning with CNNs: A Survey of Techniques and Real-World Applications
Abstract: Convolutional Neural Networks (CNNs) have emerged one of the most powerfully used tools in deep learning, particularly in image and pattern recognition tasks. CNNs are being revolutionized through deep learning resulting in a dominant architecture in computer vision as well as other various domains. This paper provides a comprehensive survey of CNN-based deep learning, its methodologies, regularizations, and computational efficiencies. We also address the challenges and future directions of CNN. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 1–5 Read article
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Design of Multispindle Drilling Head
Abstract: AbstractThis paper presents the design, analysis, and optimization of a multi-spindle drilling machine headaimed at enhancing productivity and efficiency in manufacturing processes. Engineered to drill multipleholes simultaneously, the multi-spindle head significantly reduces machining time and increasesoperational throughput, making it ideal for high-volume production environments where speed andaccuracy are essential. The design process begins with a thorough requirements analysis and materialselection to ensure the machine head can endure operational stresses while …
Published in International Journal of Manufacturing and Materials Processing · Vol. 10, Issue 2, 2024 · pp. 36–42 Read article
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Analyzing Atmospheric Particulate Matter in PortHarcourt and Omoku, Nigeria, Using Artificial NeuralNetworks and Fuzzy Logic
Abstract: Port Harcourt and Omoku, two densely populated towns in Rivers State, Nigeria, are hubs of industrial, commercial, and residential activities, characterized by the presence of oil and gas industries, educational institutions, large markets, and, in the case of Omoku, access to free electric power supply. These activities contribute to environmental degradation through industrial effluents, domestic waste, automobile emissions, gas flaring, and biomass burning, which release aerosols that form harmful particulates …
Published in International Journal of Chemical Engineering and Processing · Vol. 10, Issue 2, 2024 · pp. 16–52 Read article
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Forecasting Trends in the Stock Market by Using Deep Learning Approaches
Abstract: Accurately predicting stock market trends remains a significant challenge in the field of finance. Deep learning, a subset of machine learning, has emerged as a powerful tool for capturing complex relationships within data. What sets deep learning apart is its ability to handle vast amounts of data, recognize intricate features, and adapt to evolving patterns, all while uncovering hidden insights. At its core, deep learning uses artificial neural networks that …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 2, 2024 · pp. 22–30 Read article
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Prediction of Compressive Strength of Concrete with Decision Trees
Abstract: In the past few researchers predicted the compressive strength of concrete from its ingredients employing data driven technique like artificial neural network (ANN) and Decision Tree (DT). For Indian concrete records, only one study was available which had employed ANN for prediction. Evaluation of different performance metrics indicated that there was scope of improvement in the prediction performance. In this paper experimental data from the literature was utilized for development …
Published in International Journal of Concrete Technology · Vol. 2, Issue 1, 2016 · pp. 19–29 Read article
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Soft Computing Based Prediction of Ultimate Bearing Capacity of Footings Resting on Rock Masses
Abstract: The present study attempts to predict the ultimate bearing capacity of shallow foundations on rock masses using five different soft computing techniques namely i) random forest regression approach, ii) artificial neural networks, iii) support vector machine with polykernel, iv) support vector machine with (radial basis function) RBF kernel and v) M5P model tree. The ultimate bearing capacity was assumed to be dependent rock mass rating, unconfined compressive strength of rock, …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 5, Issue 2, 2019 · pp. 1–14 Read article
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Comparative Modeling of Pavement Surface Texture Variables Using ANN and SPSS Software
Abstract: The health of Roadway pavement surface is considered as one of the major issues for safe driving. Pavement surface condition is usually referred to micro and macro textures which enhances the friction between the pavement surface and vehicular tires, while it provides a proper drainage for heavy rainfall water. Measurement of the surface texture is not yet standardized, and many different techniques are implemented by various road agencies around the …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 2, Issue 2, 2016 · pp. 30–40 Read article