Overview
Neural networks are computational models composed of interconnected processing units, or artificial neurons, organized in layers and loosely inspired by the connectivity of biological nervous systems. Each connection carries a weight adjusted during training, and the network learns to map inputs to outputs by minimizing error through algorithms such as backpropagation, enabling it to recognize patterns, approximate complex functions, and make predictions without explicit programming of rules. Architectures range from feed-forward networks to deep and convolutional models suited to image and signal data, and they are frequently combined with optimization techniques such as genetic and nature-inspired algorithms. Neural networks underpin much of contemporary machine learning and artificial intelligence and are applied across the sciences for classification, forecasting, and inverse problems. Research relevant to this area examines genetic algorithms coupled with neural networks to estimate subsurface geophysical features, artificial neural network models for rainfall and climate analysis, and deep-learning and transfer-learning approaches to detecting plant diseases and weeds in agriculture. Further work addresses dynamic network analysis of functional brain connectivity and time-series forecasting of disease. The field links computer science, statistics, and domain-specific modelling. The journal publishes peer-reviewed research employing neural networks and related computational methods, including their application to geophysical, agricultural, and biomedical data analysis.
Research published in this journal
12 peer-reviewed articles, ranked by relevance. Each links to its DOI.
Artificial Neural Network Model for Rainfall Data Analysis During 2004-2017 in Tamil Nadu, India – Prevailing Pattern Evaluation on Climate Change
Automated Grassweed Detection in Wheat Cropping System: Current Techniques and Future Scope
Comparative Study of Deep Learning Techniques for Detecting Corn Plant Leaf Diseases Using Transfer Learning
Conservation, Creation, and Evolution: Revising the Darwinian Project
Dynamic Network Analysis of Functional Connectivity in Dementia: Unraveling Temporal Patterns and Therapeutic Implications
The Role of Cerebral Hypercarbia in the Induction of the Near-Death Experience
Nature Inspired Bargain Optimization Algorithm for Effective Interpretation of Geoelectrical Data
Creation of Music-Induced Analgesia in Chronic Pain Patients through Endogenous Opioid Production: A Narrative Review
Seasonal ARIMA model for Covid-19 pandemic Prediction in the United States
Rbm45 Phylogenetics, Protein Domain Conservation, and Gene Architecture in Clade Metazoa
Review: Non-Invasive Continuous Blood Glucose Measurement Techniques
How this research is being cited
The 12 articles above have been cited 141 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.
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2026 · Neurology International
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2026 · Journal of the Indian Society of Remote Sensing
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2025 · Communications Biology
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2025 · Artificial Life
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2025 · BMC Genomics
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2025 · Scientific Reports
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2025 · Communications Biology
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2025 · European Journal of Applied Science, Engineering and Technology
A sample of recent works citing this journal's research on Neural Networks, linking to each citing work.