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62 articles for “artificial neural network”
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Application of Hybrid Wavelet Packet-ANN in Drought Forecasting
Abstract: Drought is the most catastrophic natural disaster that has disastrous effect on human beings, environment and ecology. It is the most frequent of all the natural hazards. In this study, an attempt has been made to forecast the drought using Artificial Neural Network (ANN) for a lead time of 1-month and 6-month. Further, the pre-processing of data has been carried out using Wavelet Packet transform (WPT) and then the pre-processed …
Published in International Journal of Water Resources Engineering · Vol. 3, Issue 2, 2017 · pp. 70–80 Read article
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Comparative Study of Classification Methods Based on Feature Reduced Microarray Gene-Expression Data
Abstract: Abstract Cancer is a very complex and clinical heterogeneous disease. Now a days the research into the diagnosis and treatment of cancer have become an important issue for researchers. Cancer microarray data normally consist of samples having large number of gene expression as features. For better result in cancer classification it is very important to select relevant features. In this paper, five different types of cancer datasets are used such …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 1, Issue 2, 2015 · pp. 1–10 Read article
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Research Paper on Handwritten Character Recognition
Abstract: Handwriting recognition is the capacity of a machine to get and decipher penmanship contribution from numerous sources, for example, paper records, photos, touchscreen gadgets, and so on. Handwriting and automatic character recognition are an emerging area of research and find many applications in banks, offices and industries. The main objective of this project is to design an expert system capable of efficiently recognizing a format character of a particular type …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 7, Issue 1, 2021 · pp. 1–5 Read article
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A Review of Modeling and Data Mining Techniques Applied for Analyzing Steel Bridges
Abstract: The vibration response data measured from the structure contains uncertainties and requires different techniques for its analysis. The present study involves the comprehensive review of the model based and data mining techniques which are frequently applied by various researchers in past to solve various multi criteria decision making and analysis problems. The selection of suitable technique for specific problem is required to obtain accurate outcomes. The literature survey is done …
Published in International Journal of Software Computing and Testing · Vol. 7, Issue 1, 2021 · pp. 1–15 Read article
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Evaluation of Two Distinct AI Control Methods to Enhance Power Quality
Abstract: Artificial Intelligence techniques are the latest techniques utilized for the improvement of electrical performance. This study examines and contrasts various artificial harmonic reduction methods for source current. Artificial Intelligence may include Fuzzy logic and Artificial Neural Network. The goal of the modeling is to improve the power quality through the application of principles that cannot be expressed as "true" or "false" but rather as "partially true" called as Fuzzy logic …
Published in International Journal of Electrical Power System and Technology · Vol. 8, Issue 2, 2022 · pp. 15–26 Read article
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Multi-Modal Summarization for Digital Data
Abstract: ABSTRACTText summarization aims to abbreviate input text into a compact form. Automatic data summarization is one of the field of data mining. The increase in expansion of data communication over the net makes it crucial to create Multi-Modal Summarization (MMS) from synchronous data (text, audio, image and video). The MMS method combining the techniques of Natural Language Processing (NLP), speech processing, computer vision, and Advanced Encryption Standard (AES) encryption used …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 6, Issue 1, 2020 · pp. 28–34 Read article
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OODA Principles for Finding Unknown Malware
Abstract: This paper is planned to give a model to "OODA Principles for Finding Unknown Malware", it portrays the state's general necessities with respect to the securing and execution of intrusion prevention and detection systems with intelligence (IIPS/IIDS). This is intended to give a more profound comprehension of interruption aversion and recognition standards with knowledge may be in charge of getting, actualizing or checking such frameworks in comprehension the innovation and …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 1, Issue 2, 2015 · pp. 1–12 Read article
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Multi-class Fault Diagnosis of Rolling Element Bearing Based on Empirical Mode Decomposition and Entropy Features
Abstract: Rolling element bearings are one of the most commonly used machine elements in engineering industry. Fault detection and diagnosis of rolling element bearings is essential for prevention of malfunction and failure during operation. The present work deals with rolling element bearing fault diagnosis by using Support Vector Machine (SVM) and Artificial Neural Network (ANN). Four types of bearing conditions are considered in the present analysis: inner race fault (IR), outer …
Published in International Journal of Manufacturing and Materials Processing · Vol. 2, Issue 1, 2016 · pp. 01–10 Read article
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On the Performance of Adaptive Intelligent Wireless Senor Nodes Nanostructured Array for IoT Applications
Abstract: Nowadays practically everyone has a mobile device, and those numbers are getting higher, parallel, the number of interactive multimedia applications is also increasing, and this trend will continue in the future. Wireless sensor node data can be used for a variety of applications, including environmental monitoring, industrial automation, and smart home systems. In other circumstances, the nodes may be able to process and analyze the data locally before communicating it …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 9, Issue 2, 2023 · pp. 29–39 Read article
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Advanced Classification of Diabetic Retinopathy Using GAN and Deep Residual CNN Model
Abstract: Diabetic retinopathy (DR) is a leading cause of blindness worldwide, impacting the largest number of individuals who have diabetes. Early identification of diabetic retinopathy may help to prevent severe effects; however, the very limited availability of labeled datasets, and the possibility of overfitting of the model, presents obstacles to obtaining an accurate diagnosis. In this research, a hybrid deep learning strategy is introduced, where Generative Adversarial Networks (GANs) are used …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 8–16 Read article
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Brain-Inspired Computing: The Rise of Neuromorphic AI
Abstract: Neuromorphic computing is an emerging computing paradigm that draws inspiration from the structure and operational principles of the human brain. By integrating ideas from neuroscience, computer design, and materials science, neuromorphic systems aim to deliver high-performance, low-power computation that is suitable for smart data processing. Unlike traditional von Neumann architectures, neuromorphic hardware uses massively parallel processing, event driven computation, and adaptive learning. This paper provides an overview of neuromorphic principles, …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 12, Issue 2, 2026 Read article
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An Overview on AI in Thermal Behaviour of Polymers
Abstract: The integration of Artificial Intelligence (AI) and Machine Learning (ML) into the thermalanalysis of polymers and composite materials has transitioned from experimental curiosity to acornerstone of material science. By replacing costly and time-consuming trial-and-errorlaboratory testing with predictive modeling, AI is accelerating the development of advancedthermal interface materials, fire-retardant polymers, and aerospace-grade composites. Theprediction and optimization of the thermal behavior of polymers and composite materialsrepresent a cornerstone of modern materials science, …
Published in International Journal of Composite and Constituent Materials · Vol. 12, Issue 1, 2026 · pp. 12–16 Read article
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A Comprehensive Review of Convolutional Neural Network Architectures and Evolution
Abstract: Convolutional Neural Networks (CNNs) have become a foundational deep learning framework in computer vision because they can automatically extract layered, increasingly complex features directly from raw image data. CNNs use convolutional, pooling, and activation layers to extract spatial patterns from basic edges to intricate object components, drawing inspiration from the human visual cortex. An overview of CNNs’ basic architecture is given in this study, along with an explanation of important …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 32–40 Read article
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CyberSentinel: A Proposed Hybrid AI Framework for Real-Time Cyber Threat Intelligence
Abstract: Modern cyberattacks have grown far more sophisticated, frequent, and fast-moving than the signature-based intrusion detection systems many organizations still rely on. This paper proposes CyberSentinel, a hybrid artificial intelligence framework for real-time cyber threat intelligence (CTI) that combines three complementary techniques into a single detection pipeline: a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) module for network traffic anomaly detection, a Random Forest ensemble for structured log classification, and a transformer-based …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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The Foundations and Principles of Computational Intelligence
Abstract: Artificial intelligence (AI) assumes a driving part in security administrations. A dynamic model Intelligent Intrusion Detection System (IIDS), in view of particular AI approach for intrusion detection. The strategies that are being explored incorporate neural networks and fuzzy logic with network profiling that uses basic data mining procedures to handle the network data. Suspicious interruptions can be followed back to its unique source way and any traffic from that specific …
Published in International Journal of Analog Integrated Circuits · Vol. 1, Issue 2, 2015 · pp. 17–33 Read article
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Unlocking the Potential: Machine Learning Driven Explainable AI Applications Across Diverse Domains
Abstract: Explainable artificial intelligence (XAI) aims to make discoveries and output generated by machine learning algorithms accessible to human users in a trustworthy and easy-to-understand manner. It describes the impact of an AI model and any potential biases, helping in characterizing models with accuracy, fairness, transparency, and outcomes in decision-making powered by AI. XAI focuses on understanding the data used to train the model, its predictions, the specific elements involved in …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 1, 2023 · pp. 24–32 Read article
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AI-Optimized Reconfigurable Microstrip Bandpass Filters for DynamicSpectrum Access in 6G Networks
Abstract: The evolution toward sixth generation (6G) wireless networks introduces unprecedented demands on spectral efficiency, ultra-low latency, and real-time adaptability to dynamic radio environments. Central to this transformation is the requirement for intelligent, spectrum-agile radio front ends that can seamlessly operate across heterogeneous frequency bands. Dynamic Spectrum Access (DSA) addresses this challenge by enabling transceivers to autonomously detect, evaluate, and utilize the most suitable spectrum opportunities. The realization of DSA in …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 2, 2025 · pp. 30–38 Read article
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Intelligent Trajectories: Harnessing Artificial Intelligence for Next Generation Missile and Propellant Design
Abstract: The rapid evolution of artificial intelligence (AI) has unlocked transformative pathways for high-performance aerospace engineering, yet its integration into missile and propellant design remains nascent. This study investigates a hybrid AI-driven framework that unites physics-based modeling, data-centric learning, and multi-objective optimization to accelerate the conception, validation, and refinement of missile airframes and solid-propellant formulations. First, a physics-informed neural network (PINN) is trained on a curated database of historic missile geometries, …
Published in International Journal of Energetic Materials · Vol. 12, Issue 1, 2026 · pp. 20–26 Read article
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AI-Based Image Detection of Rice Crop Diseases Using Deep Learning and Grad-CAM
Abstract: The Indian economy relies heavily on agriculture, and rice is one of the most significant staple crops grown in the country. Nevertheless, rice cultivation faces numerous challenges due to several leaf diseases, such as bacterial leaf blight, brown spot, and leaf smut. These diseases can lead to substantial yield losses and financial burdens for farmers. Therefore, the early detection and classification of these diseases are essential to minimize crop damage …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 2, 2026 Read article
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Detailed survey on detection of Dirtiness of PV panels using different approaches
Abstract: The accumulation of dust, dirt, bird droppings, pollen, and other environmental contaminants on photovoltaic (PV) panels significantly reduces their power generation efficiency and increases operational and maintenance costs. Therefore, timely and accurate detection of the cleanliness condition of solar panels is essential for maintaining optimal energy production, improving system reliability, and extending the operational lifespan of PV installations. In recent years, considerable research interest has been directed toward automated soiling …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article