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62 articles for “artificial neural network”
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Integrated PM2.5 Estimation Using Satellite Images, Pollution Station Data, Meteorological Data and Artificial Neural Network (Case Study: Tehran City)
Abstract: ABSTRACTNowadays, the use of remote sensing to monitor airborne particulates by spatial continuity is made possible by the MODIS Sensor Aerosol Optical Depth (AOD) products. In this study, a simplified aerosol estimation model (SARA) was used to estimate the aerosol optical depth. For this purpose, the MODIS sensor data as inputs to predict PM2.5 near the surface, aerosol optical depth data and meteorological data (wind speed and direction, air temperature, …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 2, 2020 · pp. 38–50 Read article
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Evaluation of the Flow Properties of Self-Compacting Fly-ash Concrete Using Artificial Neural Network
Abstract: The purpose of this study is to examine the feasibility of using artificial neural network programming for the calculation of the fresh properties of self-compacting concrete. The input parameters of the neural network were the mix composition influencing the fresh properties of self-compacting concrete namely; the cement content, the dosages of fly-ash, water, fine aggregate, coarse aggregate, and superplasticizer. The model is founded on a multilayer feed forward neural network. …
Published in International Journal of Structural Engineering and Analysis · Vol. 7, Issue 2, 2021 · pp. 35–40 Read article
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Artificial Neural Network Model to Predict Reservoir Storage
Abstract: The rapid growth in population increases water demand thus resulting in scarcity of water which is due to improper management rather than lack of resources. Reservoir is the most important source for surface water. So, reservoir storage plays a crucial role in efficient reservoir management. Artificial neural network (ANN) is capable of simulating reservoir storage capacity. So, in present work cascade forward back propagation and feed forward back propagation network …
Published in International Journal of Water Resources Engineering · Vol. 4, Issue 1, 2018 · pp. 1–8 Read article
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DC Voltage Regulation of UPFC Using Artificial Neural Network Controller
Abstract: A feed forward Artificial Neural Network (ANN) with back propagation control is proposed to remove the peak over shoot of the DC capacitor voltage used in Unified Power Flow Controller (UPFC). Proposed ANN controller is tested for the UPFC with wind energy conversion system connected to grid using MATLAB/SIMULINK and the results are compared with the PI controller. From the results, it is clear that ANN controller helps to regulate …
Published in International Journal of Digital Communication and Analog Signals · Vol. 2, Issue 1, 2016 · pp. 13–20 Read article
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Topological Analysis of Artificial Neural Network
Abstract: ABSTRACT This paper analyzes the Artificial Neural Network (ANN) over the metric. The dimension, curvature and mappings are the three characteristics of analysis. The impact of ANN in finite and infinite space is also considered. The Euclidean metric is the limit of generalization. The structure of neuron and its mapping are presented over the finite dimension. The discrete and continuous structure of neurons is studied mathematically and its formulation is …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 5, Issue 1, 2019 · pp. 17–21 Read article
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Direction to Diagnosis by Artificial Neural Network
Abstract: ABSTRACT The diagnosis is presented by the Artificial Neural Network (ANN) in this paper. The method of diagnosis from the data over the ANN is discussed in this paper. The structure of ANN is classified by the coding and probability. Each neuron is set over the data for the diagnosis under the context of minimization of error and maximization of efficiency. Thus, the direction is presented over the mathematical analysis …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 5, Issue 1, 2019 · pp. 1–5 Read article
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Fuzzy Logic, Artificial Neural Network and Genetic Algorithm over Sylvester Law of Inertia based Data Analysis Technique
Abstract: ABSTRACT Compactness of the Fuzzy Logic (FL), Artificial Neural Network (ANN) and Genetic Algorithm (GA) is applied to analyze the data. This paper presents a foundation for the same in compact form over the Sylvester’s Law of Inertia (SLI). The sequence of FL, ANN and GA is studied for deciding the source of output data. The data interacts with the academic institutes. The academic planning is based on the existed …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 5, Issue 1, 2019 · pp. 22–29 Read article
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An Evaluative Analysis of the Utilization of Artificial Neural Networks in Forecasting Soil Engineering Characteristics: An Overview Study
Abstract: The primary objective of utilizing synthetic neural networks was to emulate the problem-solving approach akin to the human brain. This approach of employing artificial neural networks gained extensive traction within the realm of geotechnical engineering, where the engineering properties of soil play a pivotal role in ensuring the stability of various engineering structures. The primary concern revolves around the strength and deformation characteristics exhibited by soil masses. The focus lies …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 9, Issue 1, 2023 · pp. 55–63 Read article
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Statistical and Artificial Neural Network for the Determination of Thermo-Physical Properties of Fomoditine Drug Using Mixed Hydrotropy
Abstract: The experimental determination of thermo-physical properties of fomoditine drug–mixed hydrotrope concentration mixture is very time consuming as well as tedious process. Any tool helpful in estimation of these properties without experimentation can be of immense utility. In present work, other tools of determination of properties of fomoditine drug–mixed hydrotrope concentration blends were tried. A traditional statistical technique of linear regression (principle of least squares) was used to estimate the specific …
Published in International Journal of Chemical Engineering and Processing · Vol. 1, Issue 2, 2015 · pp. 1–6 Read article
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Introduction to Kinematics using Artificial Neural Network
Abstract: A neural network is a machine designed to simulate how a specific process or function ofinterest is performed by the brain. To achieve good efficiency, we use a large interconnectionof simple computer cells called "neurons" or "processing units." Therefore, a neural networkviewed as an adaptive machine can be described as a massively parallel distributedprocessor comprising simple processing units with a natural propensity to store experimentalknowledge and make it available for …
Published in International Journal of Analog Integrated Circuits · Vol. 5, Issue 2, 2019 · pp. 1–5 Read article
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Artificial neural network based classification of varieties of thin and thick fabric images
Abstract: Abstract: The proposed work focuses on classification of varieties of thin and thick fabric materials from images. The morphological operations such as erosion and dilation are performed. Morphological features namely, avg_moments, average_area, roundness, max_area, average_perimeter, average_eccentricity, circularity and average_equivalent_diameter are extracted. The prediction is carried out using artificial neural network. The classification rates of 84.84% and 90.90% are obtained for thin and thick fabric images. The classification rates for varieties …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 1, 2018 · pp. 31–41 Read article
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Predictive Modeling of Dengue Mosquito Populations Using Artificial Neural Networksfor Effective Zapping Solutions
Abstract: The World Mosquito Programme highlights the significant global threat posed by dengue fever, estimating that over half of the world's population is at risk, with approximately 390 million cases reported annually. In 2023, India witnessed a substantial increase in dengue cases, recording over 270,000 cases compared to 74,000 in 2017. Dengue Virus (DENV) transmission occurs through Aedes Aegypti Mosquito bites, and with no specific treatment or vaccine available, effective management …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 10, Issue 1, 2024 · pp. 27–36 Read article
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Detecting COVID_19 in X-ray images using artificial neural network
Abstract: In this paper, we propose a method for detecting COVID-19, which is most important for now days in lowering mortality rates. COVID-19 had a rapid impact on our daily lives, businesses, and global trade and transportation. Chest CT scans and CT x-rays reveal particular radiographic abnormalities in people with COVID-19 by means of faster and more efficient representation of the patient's lung that enables for the detection of viral phenomena. …
Published in International Journal of Broadband Cellular Communication · Vol. 8, Issue 1, 2022 · pp. 32–38 Read article
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Artificial Neural Networks based Four-Leg Matrix Converter for Linear and Non-Linear Load
Abstract: The 4-leg matrix converter, which it is capable of providing a 3-phase plus neutral supply from a standard balanced 3-phase source . Tralatitious 3x3 matrix converters deliver bounded use in this application as they are only capable of supplying a poised three-phase payload. It would be suitable to be able to power unbalanced and nonlinear loads ,requiring that the converter provides a neutral connection .This goal can be achieved by …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 2, Issue 1, 2016 · pp. 45–53 Read article
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A Review on Computational Intelligence and its Applications
Abstract: Abstract:Computational intelligence (CI) is a term used to describe a computer's capacity to learn a particular task via data or experimental observation. Although it is frequently used as a synonym for soft computing, computational intelligence is still not well defined. Soft computing, commonly referred to as computational intelligence, is a type of computing that is based on how people learn. Computers become more intelligent when they learn from procedures based …
Published in International Journal of Computer Aided Manufacturing · Vol. 8, Issue 1, 2022 · pp. 27–30 Read article
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Short-Term Load Forecasting By Using ANN
Abstract: Load forecasting play an impartment role in power system planning, operation and control. Short-term load forecasting is an important basis of the secure and economic operation in power systems. Accurate load forecasting is helpful to improve the security and economic effect of power systems and can reduce the cost of generation. Therefore, finding an appropriate load forecasting method to improve accuracy of forecasting has important application value. This paper explains …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 1, Issue 1, 2015 · pp. 31–36 Read article
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NEURAL NETWORK APPROACH FOR PROCESSING SUBSTATION ALARMS
Abstract: This paper studies the method of processing of alarms in an electric substation using artificial neural networks (ANN) as a tool. Whenever there is a fault in the power system, or there is a significant change in the network, alarms are issued to the substation operators, with each alarm being associated with a message. This is the driving force for research and experiments regarding innovations of more sophisticated methods of …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 1, Issue 1, 2015 · pp. 21–28 Read article
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Application of Artificial Neuron Network in roughness prediction: A case study in turning of stainless steel
Abstract: - Artificial neural networks offer a practical and efficient way to choose the best machining parameters for the turning process in order to reduce surface roughness, the resulting cutting forces, and maximize tool life. Surface roughness is a significant aspect in the evaluation of cutting performance and plays a significant role in the manufacturing process. The goal of this project is to create a model based on an Artificial Neural …
Published in International Journal of Computer Aided Manufacturing · Vol. 8, Issue 1, 2022 · pp. 21–26 Read article
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An Integrated Machine Learning and IoT-Based Framework for Predictive Urban Water Demand Management and Distribution Optimization
Abstract: Abstract Urban water resource management has become increasingly complex due to rapid urbanization, population growth, climate variability, and aging infrastructure. Conventional water management approaches are often reactive, inefficient, and incapable of handling real-time fluctuations in demand and supply. This study proposes an integrated framework that combines machine learning (ML) techniques with Internet of Things (IoT)-based real-time monitoring to enhance water demand prediction and optimize distribution systems in urban environments. The …
Published in International Journal of Water Resources Engineering · Vol. 12, Issue 1, 2026 Read article
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Hybrid Machine Learning Model for EfficientBotnet Attack Detection in IoT Environment
Abstract: The rapid advancement and widespread adoption of internet technologies have led to a surge in cyber-attacks, with botnet attacks emerging as particularly detrimental. Identifying botnet activities is increasingly challenging due to the diverse attack vectors and the evolving nature of malware. As the Internet of Things (IoT) continues to expand, network devices become more vulnerable to these sophisticated attacks, resulting in significant security breaches and financial losses. In order to …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 31–38 Read article