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408 articles for “artificial neural network”
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Stochastic Modelling and Seasonal Artificial Neural Networks for the Prediction of Monthly Rainfall in India
Abstract: Stochastic modelling for the prediction of monthly rainfall levels with machine learning is dealt within this paper.Rainfall is essential for agriculture and the survival of all living things. Accurate forecasting of rainfall is essential for proper planning and the execution of agricultural activities. Periods of dry weather without rainfall can have major consequences on water supply affecting ground water levels and agriculture. Stochastic modelling has been widely used to time …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 96s–103s Read article
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Review on Digital Filter Design Using Artificial Neural Network
Abstract: AbstractThis paper provides a survey report on designing digital FIR filters with the help of artificial neural network (ANN) proposed by many researchers who gives a better results and easy way to design a filter. It includes types of filters, window techniques, artificial neural network, comparative analysis of various existing work. This paper gives a better way to analyze various techniques used to design FIR filters. This survey report provides …
Published in Journal of Communication Engineering & Systems · Vol. 6, Issue 2, 2016 · pp. 9–15 Read article
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Forecasting of Factors Affecting Thermiston Work Productivity Estimation by Using Artificial Neural Network
Abstract: The research aims to find factors affecting of Thermiston work productivity and the derivation of an equation to predict the rates of Thermiston work productivity by using artificial neural network technology and compared with traditional methods. The Artificial Neural Network with multilayer by back-propagation error technique for modeling the productivity estimation is used, it is founded that the ANN are able to manage to, can predict the productivity for Thermiston …
Published in Journal of Construction Engineering, Technology & Management · Vol. 7, Issue 1, 2017 · pp. 10–21 Read article
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Modelling of Flood in Lagos using Artificial Neural Network
Abstract: Flooding events have caused havoc to live and properties in recent times. Flooding could be caused by several factors some of which are rainfall, temperature, and relative humidity, which lead to rise in water level. The method of artificial neural networks (ANN) was used in this work to model flood occurrence in Lagos, Nigeria. Meteorological data were collected from the Nigeria Meteorological Agency (NIMET) and Nigeria Hydrological survey Agency (NHSA) …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 7, Issue 2, 2018 · pp. 50–57 Read article
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Design and Simulation of Artificial Neural Network (ANN) Based Speed Control for an Induction Motor Taking Core Loss and Stray Load Losses into Account
Abstract: Indirect field oriented control scheme has been preferred due to its superior performance for Induction Motor. Core Loss and stray load losses are generally neglected in the mathematical model of induction motor. But it should be consider in the mathematical model of induction motor to precisely control the torque and flux. Conventional PI controller has overshoot effect at the transient period of the speed response curve. Artificial Neural Network (ANN) …
Published in Journal of Control & Instrumentation · Vol. 6, Issue 3, 2015 · pp. 13–22 Read article
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Optimization Study by Response Surface Methodology and Artificial Neural Network on the Culture Parameters of Citric Acid Bioproduction from Sweet Potato Peels
Abstract: In the cause of this research work, two steps enzymatic hydrolysis of sweet potato peel was carried out respectively. The effect of α-amylase dose, reaction time, and reaction temperature and biomass weight on glucose concentration was investigated carefully. The response surface methodology (REM) predicted the highest reducing sugar concentration at liquefaction to be 74 g/L, at the following optimized conditions; temperature of 45°C, α-amylase dose 0.7 %v/v, biomass weight 22.345 …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 9, Issue 1, 2022 · pp. 30–38 Read article
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Thermal Performance of Flat Tube Louver Fin Heat Exchanger using Artificial Neural Network
Abstract: In this paper, an application of artificial neural networks (ANNs) is presented to predict the outlet temperatures on both fluid side of flat tube louver fin type heat exchanger used in flat tube louver fin heat exchanger. A validated numerical code is developed using MATLAB to generate huge data sets which gives outlet temperature of both the fluids. Three-layer feed-forward back propagation neural network is developed to model the thermal …
Published in Journal of Thermal Engineering and Applications · Vol. 4, Issue 3, 2017 · pp. 6–12 Read article
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Artificial Neural Networks for Brain Controlled Artificial Legs and Brain Computer Interface (BCI)
Abstract: AbstractThe whole system is guarded with the support of highly developed microcontrollers and digital signal processors. The signals square measure taken out from the human brain with the assistance of electroencephalography technique. The person will perform operations like walking, running etc. simply by their thought. These methods are going to be significantly appropriate for people who lose their legs in accidents and the planned system is hundred percentages possible within …
Published in Journal of Advancements in Robotics · Vol. 4, Issue 2, 2017 · pp. 1–4 Read article
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BREAKDOWN VOLTAGE TEST OF DIFFERENT SOLID INSULATING MATERIALS USING ARTIFICIAL NEURAL NETWORK MODEL
Abstract: In this paper we are presenting Artificial Neural Network (MFNN) model which has different possible inputs affecting the breakdown voltage that are working temperature, the insulating material thickness, dielectric strength of insulating material, volume resistivity of materials, dissipation factor, conductivity of materials, and the materials relative permittivity that also predicts the breakdown voltage as a function of all these inputs parameters. It is important to train the Artificial Neural Network …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 6, Issue 2, 2018 · pp. 22–29 Read article
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Predicting Software Reliability using Artificial Neural Networks: A Review
Abstract: AbstractSoftware reliability has become a major concern for all the software systems. Predicting software reliability has become a major challenge for both the software developers and the engineers. Before the software is dispensed to the market/customers, it is thoroughly checked for any errors and if errors are there, they are thereby removed. For the purpose of reliability estimation certain mathematical software reliability models have been proposed for estimating the reliability …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 6, Issue 2, 2019 · pp. 14–19 Read article
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OQPMSAV: Opportunistic Quality of Services Provisioning for Multimedia Services using Artificial Neural Network
Abstract: Vehicular ad hoc network is used to provide services related to traffic safety and user requirements. In VANET, applications are designed for users from various domains automobile company, road safety authority, advertisement industries, personal entertainment. Applications developer requires efficient utilization of available networking resources. VANET is witnessed of continuous support form researchers, developer, government authorities and vehicles manufactures. In VANET, vehicles are designed to move at high speed which causes …
Published in Journal of Communication Engineering & Systems · Vol. 8, Issue 1, 2018 · pp. 29–42 Read article
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A Novel Software Cost Estimation Model Based on the Hybrid of Artificial Neural Network and Firefly Algorithm
Abstract: Software cost estimation is the prediction of software development effort and software development time required to develop a software project. Software cost estimation is a basic and important task for both successful execution of software development life cycle and its management interms of its cost & time. Accurate software cost estimation is considered to be a difficult task as the information about the software project to be developed at the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 38–45 Read article
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Optimization and Modelling of Process Parameters for Turning Operation on Cnc Lathe for ASTM A242 Type-2 Alloy Steel by Regression Analysis and Artificial Neural Network
Abstract: The purpose of this project is focussed on the modelling of cutting conditions to get the lowest surface roughness in turning ASTM A242 TYPE-2 ALLOYS STEEL by Artificial Neural Network and Regression Analysis method on the CNC lathe. The process of metal cutting has been well researched over the years; relatively small research has been carried out on the cutting of alloy of ASTM A242 grade materials. In this study, …
Published in Journal of Advancements in Robotics · Vol. 2, Issue 2, 2015 · pp. 40–51 Read article
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Automatic License Plate Recognition using Video Sequences as Input and Artificial Neural Network as Recognition Technique
Abstract: AbstractALPR system is used to automatically extract the number plate of a vehicle. This can be achieved by using different techniques that are employed in the field of image processing. ALPR method consists of 4 basic stages. The first stage of the system is the acquisition of an image of the vehicle. After that, the next step is license plate localization and then segmentation of the extracted license plate is …
Published in Current Trends in Signal Processing · Vol. 8, Issue 2, 2018 · pp. 25–38 Read article
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Optimization of Green Sand Casting Process Parameters by Artificial Neural Network
Abstract: In this paper, artificial neural network (ANN) is used to train the network which can predict the casting defect. L27 orthogonal array is used as input matrix for training of neural network. NN tool is used to train the network for prediction of defects. Major defects observed on shop floor were; misrun, blowholes, inclusions and porosity. Moisture, permeability, LOI, compressive strength, volatile content, vent holes, pouring time, pouring temperature, mould …
Published in Trends in Mechanical Engineering & Technology · Vol. 6, Issue 2, 2016 · pp. 75–80 Read article
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Design of Beam using Artificial Neural Network based Approach
Abstract: Recent developments in artificial neural network (ANN) have opened up new possibilities in the field of structural engineering. This paper demonstrates the applicability of ANN for the design of beams subjected to moment and shear. An attempt has been made to capture the mapping between the design variables using ANN. There is no direct method for design of beams. A feed forward network and back propagation training algorithm has been …
Published in Recent Trends in Civil Engineering & Technology · Vol. 4, Issue 3, 2014 · pp. 1–6 Read article
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An Overview of Artificial Neural Network and its Applications
Abstract: This paper presents an overview of Artificial Neural Network (ANN). The study of neurons and its discrete representation by the set theory is the key objective of this paper. New data structure technique is proposed in this paper by using the mechanism of (ANN). The finite dimension of the field is generalized in this paper. The linear transformation and the representation of the vector basis are applied to propose the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 2, 2020 · pp. 17–20 Read article
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Stock Market Forecasting Using Artificial Neural Networks (ANNs): A Review
Abstract: AbstractThis paper reviews all recent work done for stock market prediction using machine learning and artificial intelligence (AI). Artificial neural networks (ANNs), a field of artificial intelligence (AI), is relatively latest, dynamic and promising technique in stock market forecasting, an area that has been of much research. From this literature review, it is concluded that ANNs is very valuable for predicting world stock markets.Keywords: artificial neural network (ANNs), stock market, …
Published in Journal of Computer Technology & Applications · Vol. 4, Issue 2, 2013 · pp. 18–29 Read article
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An Efficient Fault Detection and Localization System for Three-Phase Transmission Line using Arduino and Artificial Neural Networks
Abstract: This paper presents an efficient fault detection and localization system for a three-phase transmission line using Arduino and artificial neural networks. Theproposed system is designed to detect and localize faults in real-time, reducing the downtime and improving the reliability of the power system. The system consists of three main components: the fault detection unit, the fault classification unit, and the fault localization unit. The fault detection unit uses Arduino microcontroller …
Published in Recent Trends in Electronics Communication Systems · Vol. 9, Issue 3, 2022 · pp. 35–42 Read article
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Energy and Exergy Analysis of Ammonia Water Operated Vapour Absorption Refrigeration System Using Artificial Neural Network Approach
Abstract: In this study, energy and exergy analysis have been performed of the ammonia-water operated vapour absorption refrigeration (VAR) system. Authors have trained artificial neural network (ANN) for predicting thermodynamic properties (specific enthalpy and specific entropy) of working fluid (ammonia-water). Authors have achieved coefficient of multiple determination (R2) value 0.9999 and the root mean square error (RMSE) value 0.00211 for input data set of saturated liquid and R2 value 0.999999 and …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 2, Issue 1, 2015 · pp. 7–20 Read article