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416 articles for “neural network method”
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Optimizing Glass to Metal Composite Seal Performance: An integrated Approach with Artificial Neural Network, Multiple Regression, and Taguchi
Abstract: Composite materials, particularly glass to metal composites, are critical components in solar receiver tubes, where vacuum leakage can significantly compromise the efficiency of solar plants. This research addresses the technical barriers associated with the development of durable and high-quality glass to metal composite seals. We investigate the principles that can enhance the physical and chemical properties of these composite seals, focusing on the incorporation of TiO2 and MgO nanoparticles into …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 418–435 Read article
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Review Paper on Efficient Quality Inspection of Food Products Using Neural Network Classification
Abstract: AbstractWith the increasing competiveness in the field of food production growing at a faster pace across the globe, quality is one of the most desirable features that a product should possess. The ability to produce quality as well as safety food is the most prerequisite factors for both, national and international market. This paper explains the recently developed approaches and latest research efforts related to the assessment of the quality …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 4, Issue 1, 2017 · pp. 1–14 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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Identification of Potato Plant Leaf Disease Using Different Artificial Intelligence (AI) Techniques: A Review
Abstract: One of the nation's most vital industries is agriculture. Employment possibilities are abundant in emerging nations like India. The livelihoods of nearly 70% of the global population depend on agriculture. In this study, we have evaluatednumerous articles that have been released on potato plant leaf disease (PLD)diagnosis and classification utilising machine learning (ML)or Deep Learning (DL)methods. There are several causes of leaf diseases in plants, including bacteria, viruses, fungus, and …
Published in Journal of Open Source Developments · Vol. 10, Issue 3, 2023 · pp. 7–19 Read article
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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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Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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An Effective Convolutional Neural Network for Identifying Cancer Blood Disorder Cells Using Microscopic Images
Abstract: Blood, bone marrow, and lymphatic systems are all impacted by hematological cancer is known as a cancer blood disorder. Blood malignancies and various blood disorders pose significant health challenges across all age groups. Early disease detection is essential for effective cancer blood disorder treatment and management. If a blood cancer is not identified in time, it may be hazardous. It results in abnormal white blood cell production by the bone …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 29–35 Read article
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A Study on Social Network Mining
Abstract: AbstractA rapid increase has been seen in the recent decade in the usage of social media. Web and web 2.0 has made it easy for users to reach out to Twitter, Facebook and other social media platforms. Most of the users depend on these social media platforms for news and opinions on trending topics. This type of dependence on these social media platforms have produced large amount of data in …
Published in Journal of Advanced Database Management & Systems · Vol. 6, Issue 2, 2019 · pp. 36–39 Read article
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FACE EMOTION RECOGNITION TO DETECT DEPRESSION
Abstract: In the current competitive world, one of the most familiar and grave mental illness we encounter in humans is Depression also called as major depression or major depressive disorder. It makes you feel depressed and disinterested all the time, which has a bad impact on your thoughts and behaviour. Thus affecting not only the victim but also people associated with them, such as family, friends and society. If not treated …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 1–14 Read article
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Prediction and Comparative Analysis of Thermal Conductivity of Jatropha Oil-based Hybrid Nanofluid by Multivariable Regression and ANN
Abstract: In the present study, a multivariable regression (MR) and artificial neural network (ANN) method was used to predict the thermal conductivity of Jatropha oil-based ZnO-Ag hybrid nanofluid. Firstly, the ZnO-Ag hybrid nanoparticles were synthesized and mixed in the jatropha oil to prepare various nanofluids at different volume concentrations (F) ranging from 0.05 to 0.20%. The stability and thermal conductivity of the prepared nanofluids were investigated. Wide ranges of temperature and …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 32–39 Read article
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Survey of Techniques for Clustering and Classification of ECG using WEKA
Abstract: ECG analysis can be done for automatic detection of abnormality in cardiac activity. This can be helpful in generating alert for saving a precious life. Various techniques have been proposed in literature for feature detection and classification such as; fuzzy logic methods, artificial neural networks (ANN), and support vector machines (SVM), wavelet transform, Hilbert transform, etc. Recently, numerous researches and techniques have been developed for analyzing the ECG signal on …
Published in Journal of Microcontroller Engineering and Applications · Vol. 3, Issue 2, 2016 · pp. 14–19 Read article
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Survey of Predictive Models for Safe Route Predicting Using Machine Learning Techniques
Abstract: Safe route prediction is essential for the well-being and security of individuals in urban and rural environments. Machine learning techniques leverage historical data, real-time information, and algorithms to estimate the safety levels of different routes. The objective of safe route planning is to minimize risks, including crime-prone areas and accidents, reducing potential harm, property damage, and emotional distress. However, challenges arise from the complex and dynamic nature of urban environments, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 1, 2024 · pp. 13–22 Read article
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Comparison of RSM and ANN Modeling Approaches in Predicting the Laser Phase Transformation Hardening Parameters on the Heat Input and Hardened-Bead Profile Quality of Unalloyed Titanium
Abstract: In the present work, laser transformation hardening (LTH) of unalloyed titanium, nearer to ASTM Grade 3 of chemical composition was investigated using CW 2kW, Nd: YAG laser. The laser process variables such as laser power, scanning speed, and focused position play a major role in deciding the laser hardened bead quality. Two methods, Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were used to predict the heat input and …
Published in Journal of Materials & Metallurgical Engineering · Vol. 5, Issue 1, 2015 · pp. 36–59 Read article
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Evaluation of Coefficient of Performance of Water– Carrol Vapor Absorption Refrigeration System Using Artificial Neural Network approach
Abstract: Normal 0 false false false EN-US X-NONE X-NONE The aim of this work is to apply expert system methods, like artificial neural network (ANN), for evaluating the coefficient of performance (COP) of water-carrol (lithium bromide-ethylene glycol)-based vapor absorption refrigeration system. Theoretical performance analysis of vapor absorption refrigeration system is too complex since very tedious second-order mathematical differential equations are used. In order to simplify this complex process, artificial neural networks …
Published in Trends in Mechanical Engineering & Technology · Vol. 2, Issue 3, 2012 · pp. 29–37 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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A Novel Strategy for Weight Initialization in Sigmoidal Feed-forward Artificial Neural Networks
Abstract: In this paper, a novel method of weight initialization is proposed. The proposed method of weight initialization distributes the initial weights and thresholds in such a manner that they lie in different regions of the activation function used at the hidden layer. The proposed method is compared with six other popular weight initialization methods on ten function approximation problems using the RPROP (Resilient Back-propagation) and Levenberg-Marquardt algorithms for training. Two …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 62–75 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Enhancing Data Security Via the Application of Back- Propagation Feed-Forward Methods in Encryption
Abstract: The computer society uses a variety of automated methods for file security and data storage. Several organisations are concerned about the information exchange via an unsecured network for a distributed architecture, such as the time-sharing and real-time system. Probably the most crucial element that contributes to effective security is cryptography. Using a constant weighted factor for boosting the factor, the study aims at extending or updating the earlier presented Artificial …
Published in Journal of Open Source Developments · Vol. 9, Issue 3, 2022 · pp. 13–17 Read article
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Measurement of Program Outcomes Attainment for Engineering Graduates by using Neural Networks
Abstract: AbstractThis paper aims to provide an evaluation method for the attainment of program objectives for engineering graduates as defined by NBA (National Board of Accreditation). As NBA requires specific evaluation techniques and measurement methods for measuring the attainment of course outcomes, program outcomes and program educational outcomes; this paper provides a solution of the measurement techniques using neural networks. The performance of all the students of a batch can be …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 21–24 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article