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1. |
Record Nr. |
UNISALENTO991001165639707536 |
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Autore |
Eeckman, Frank H. |
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Titolo |
Neural systems : analysis and modeling / edited by Frank H. Eeckman |
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Pubbl/distr/stampa |
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Boston ; London ; Dordrecht : Kluwer Academic Publishers, c1993 |
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ISBN |
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Descrizione fisica |
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vii, 465 p. : ill. ; 25 cm. |
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Classificazione |
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Disciplina |
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Soggetti |
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Neural circuitry-Computer simulation - Congresses |
Neural networks (Neurobiology) - Congresses |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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"The collected papers of the 1991 Conference on Analysis and Modeling of Neural Systems (AMNS) and the papers presented at the satellite symposium on compartmental modeling, held July 23-26, in San Francisco, California" - Introd. |
Includes bibliographical references and index |
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2. |
Record Nr. |
UNINA9910851982603321 |
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Autore |
Pandit Manjaree |
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Titolo |
Artificial Intelligence and Sustainable Computing : Proceedings of ICSISCET 2023 / / edited by Manjaree Pandit, M. K. Gaur, Sandeep Kumar |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (714 pages) |
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Collana |
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Algorithms for Intelligent Systems, , 2524-7573 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Computational intelligence |
Electronic circuits |
Cooperating objects (Computer systems) |
Internet of things |
Machine learning |
Computational Intelligence |
Electronic Circuits and Systems |
Cyber-Physical Systems |
Internet of Things |
Machine Learning |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Preface -- Contents -- About the Editors -- 1 A Novel Intelligence System for Hybrid Crop Suitable Landform Prediction Using Machine Learning Techniques and IoT -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Dataset Description -- 5 Feature Engineering -- 6 Experiments -- 6.1 Logistic Regression -- 6.2 K-Nearest Neighbours (KNN) -- 6.3 Extreme Gradient Boosting (XGBoost) -- 6.4 Implementation in Cloud -- 7 Results and Discussion -- 8 Conclusion -- 9 Future Work -- References -- 2 Indian Annual Report Assessment Using Large Language Models -- 1 Introduction -- 1.1 Problem Statement -- 1.2 Objective -- 1.3 Contribution -- 2 |
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Related Work -- 3 Methodology -- 3.1 Dataset Preparation -- 3.2 Class Labels -- 4 Results -- 4.1 Fine-Tuning Language Model -- 4.2 Sentence Transformers |
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Sommario/riassunto |
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This book presents high-quality research papers presented at the 5th International Conference on Sustainable and Innovative Solutions for Current Challenges in Engineering and Technology (ICSISCET 2023) held at Madhav Institute of Technology & Science (MITS), Gwalior, India, during October 21–22, 2023. The book extensively covers recent research in artificial intelligence (AI) that knit together nature-inspired algorithms, evolutionary computing, fuzzy systems, computational intelligence, machine learning, deep learning, etc., which is very useful while dealing with real problems due to their model-free structure, learning ability, and flexible approach. These techniques mimic human thinking and decision-making abilities to produce systems that are intelligent, efficient, cost-effective, and fast. The book provides a friendly and informative treatment of the topics which makes this book an ideal reference for both beginners and experienced researchers. |
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