BOOKS - The Future of Artificial Neural Networks
The Future of Artificial Neural Networks - Indrajit Ghosal, Arun Mittal, Hemlata Jain 2024 PDF Nova Science Publishers BOOKS
ECO~14 kg CO²

1 TON

Views
26198

Telegram
 
The Future of Artificial Neural Networks
Author: Indrajit Ghosal, Arun Mittal, Hemlata Jain
Year: 2024
Pages: 222
Format: PDF
File size: 18.0 MB
Language: ENG



Pay with Telegram STARS
The Future of Artificial Neural Networks: A Paradigm Shift in Understanding Technology Evolution Introduction Artificial neural networks (ANNs) have been a crucial part of modern technology for decades, revolutionizing various industries such as healthcare, finance, marketing, and transportation. However, as we continue to develop and refine these networks, it's essential to understand their evolution and how they will shape our future. In "The Future of Artificial Neural Networks," we explore the need for a personal paradigm for perceiving the technological process of developing modern knowledge and its significance in ensuring humanity's survival. This book provides an in-depth analysis of the current state of ANNs, their potential applications, and the challenges that come with their development.
Будущее искусственных нейронных сетей: смена парадигмы в понимании эволюции технологий Введение Искусственные нейронные сети (ANN) были важной частью современных технологий на протяжении десятилетий, революционизируя различные отрасли, такие как здравоохранение, финансы, маркетинг и транспорт. Однако по мере того, как мы продолжаем развивать и совершенствовать эти сети, важно понимать их эволюцию и то, как они будут формировать наше будущее. В «Будущем искусственных нейронных сетей» исследуем необходимость личностной парадигмы восприятия технологического процесса развития современного знания и его значение в обеспечении выживания человечества. В этой книге представлен глубокий анализ текущего состояния ИНС, их потенциальных применений и проблем, возникающих при их разработке.
L'avenir des réseaux neuronaux artificiels : un changement de paradigme dans la compréhension de l'évolution des technologies Introduction s réseaux neuronaux artificiels (ANN) ont été une partie importante des technologies modernes pendant des décennies, révolutionnant divers secteurs tels que la santé, la finance, le marketing et les transports. Cependant, alors que nous continuons à développer et à améliorer ces réseaux, il est important de comprendre leur évolution et comment ils façonneront notre avenir. Dans « L'avenir des réseaux neuronaux artificiels », nous explorons la nécessité d'un paradigme personnel de la perception du processus technologique du développement de la connaissance moderne et de son importance pour la survie de l'humanité. Ce livre présente une analyse approfondie de l'état actuel des INS, de leurs applications potentielles et des problèmes rencontrés dans leur développement.
futuro de las redes neuronales artificiales: un cambio de paradigma en la comprensión de la evolución de la tecnología Introducción redes neuronales artificiales (ANN) han sido una parte importante de la tecnología moderna durante décadas, revolucionando diversas industrias como la salud, las finanzas, el marketing y el transporte. n embargo, a medida que continuamos desarrollando y mejorando estas redes, es importante comprender su evolución y cómo darán forma a nuestro futuro. En «futuro de las redes neuronales artificiales» exploramos la necesidad de un paradigma personal para percibir el proceso tecnológico del desarrollo del conocimiento moderno y su importancia para garantizar la supervivencia de la humanidad. Este libro presenta un análisis profundo del estado actual del INS, sus posibles aplicaciones y los problemas que surgen en su desarrollo.
Il futuro delle reti neurali artificiali: cambiamento di paradigma nella comprensione dell'evoluzione tecnologica Introduzione reti neurali artificiali (ANN) sono state una parte importante della tecnologia moderna per decenni, rivoluzionando diversi settori come salute, finanza, marketing e trasporti. Tuttavia, mentre continuiamo a sviluppare e migliorare queste reti, è importante comprendere la loro evoluzione e il modo in cui essi modelleranno il nostro futuro. Il Futuro delle Reti Neurali Artificiali esplora la necessità di un paradigma personale della percezione del processo tecnologico per lo sviluppo della conoscenza moderna e la sua importanza per la sopravvivenza dell'umanità. Questo libro fornisce un'analisi approfondita dello stato attuale dell'INS, delle loro potenziali applicazioni e dei problemi che si verificano nel loro sviluppo.
Die Zukunft künstlicher neuronaler Netze: Paradigmenwechsel im Verständnis der Technologieentwicklung Einführung Künstliche neuronale Netze (ANN) sind seit Jahrzehnten ein wichtiger Bestandteil moderner Technologien und revolutionieren verschiedene Branchen wie Gesundheitswesen, Finanzen, Marketing und Verkehr. Wenn wir diese Netzwerke jedoch weiterentwickeln und verbessern, ist es wichtig, ihre Entwicklung zu verstehen und zu verstehen, wie sie unsere Zukunft gestalten werden. In „Die Zukunft der künstlichen neuronalen Netze“ untersuchen wir die Notwendigkeit eines persönlichen Paradigmas der Wahrnehmung des technologischen Prozesses der Entwicklung des modernen Wissens und seine Bedeutung für das Überleben der Menschheit. Dieses Buch bietet eine eingehende Analyse des aktuellen Zustands von INS, ihrer potenziellen Anwendungen und der Herausforderungen, die sich aus ihrer Entwicklung ergeben.
העתיד של רשתות עצביות מלאכותיות: שינוי פרדיגמה בהבנת האבולוציה של מבוא טכנולוגי רשתות עצביות מלאכותיות (ANS) היו חלק חשוב של טכנולוגיה מודרנית במשך עשרות שנים, אולם, כשאנו ממשיכים לפתח ולזקק את הרשתות הללו, חשוב להבין את האבולוציה שלהן וכיצד הן יעצבו את עתידנו. ב- "The Future of Artificial Neural Networks', אנו חוקרים את הצורך בפרדיגמה אישית לתפיסה של התהליך הטכנולוגי של התפתחות הידע המודרני וחשיבותו בהבטחת הישרדות האנושות. ספר זה מספק ניתוח מעמיק של המצב הנוכחי של ANS, היישומים הפוטנציאליים שלהם והבעיות שנתקלו בהם בהתפתחותם.''
Yapay nir Ağlarının Geleceği: Teknolojinin Evrimini Anlamada Bir Paradigma Değişimi Giriş Yapay sinir ağları (YSA'lar), onlarca yıldır modern teknolojinin önemli bir parçası olmuş ve sağlık, finans, pazarlama ve ulaşım gibi çeşitli sektörlerde devrim yaratmıştır. Ancak, bu ağları geliştirmeye ve geliştirmeye devam ederken, evrimlerini ve geleceğimizi nasıl şekillendireceklerini anlamak önemlidir. "Yapay nir Ağlarının Geleceği'nde, modern bilginin gelişiminin teknolojik sürecinin algılanması ve insanlığın hayatta kalmasını sağlamadaki önemi için kişisel bir paradigma ihtiyacını araştırıyoruz. Bu kitap, YSA'ların mevcut durumunun, potansiyel uygulamalarının ve gelişimlerinde karşılaşılan sorunların derinlemesine bir analizini sunmaktadır.
مستقبل الشبكات العصبية الاصطناعية: تحول نموذجي في فهم تطور مقدمة التكنولوجيا كانت الشبكات العصبية الاصطناعية (ANNs) جزءًا مهمًا من التكنولوجيا الحديثة لعقود، مما أحدث ثورة في مختلف الصناعات مثل الرعاية الصحية والتمويل والتسويق والنقل. ومع ذلك، بينما نواصل تطوير وصقل هذه الشبكات، من المهم فهم تطورها وكيف ستشكل مستقبلنا. في «مستقبل الشبكات العصبية الاصطناعية»، نستكشف الحاجة إلى نموذج شخصي لتصور العملية التكنولوجية لتطور المعرفة الحديثة وأهميتها في ضمان بقاء البشرية. يقدم هذا الكتاب تحليلاً متعمقًا للحالة الحالية للشبكات الوطنية الوطنية وتطبيقاتها المحتملة والمشاكل التي واجهتها في تطويرها.
人工神經網絡的未來:理解技術演變的範式轉變介紹人工神經網絡(ANN)幾十來一直是現代技術的重要組成部分,徹底改變了醫療保健、金融、市場營銷和運輸等不同行業。然而,隨著我們繼續發展和完善這些網絡,了解它們的演變以及它們將如何塑造我們的未來至關重要。在「人工神經網絡的未來」中,探討了個人範式對現代知識發展過程感知的必要性及其對人類生存的重要性。本書深入分析了INS的當前狀態,其潛在應用以及開發過程中遇到的問題。

You may also be interested in:

Applied Deep Learning Design and implement your own Neural Networks to solve real-world problems
Introduction to Lattice Algebra With Applications in AI, Pattern Recognition, Image Analysis, and Biomimetic Neural Networks
New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms
New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms
Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification by Antonios K. Alexandridis (2014-05-05)
New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics (Studies in Computational Intelligence Book 1149)
Applied Artificial Neural Network Methods For Engineers And Scientists Solving Algebraic Equations
Neural Network Driven Artificial Intelligence Decision Making Based on Fuzzy Logic
Think AI Explore the flavours of Machine Learning, Neural Networks, Computer Vision and NLP with powerful python libraries
Fuzzy Neural Networks for Real Time Control Applications Concepts, Modeling and Algorithms for Fast Learning
The Python Bible 7 in 1 Volumes One To Seven (Beginner, Intermediate, Data Science, Machine Learning, Finance, Neural Networks, Computer Vision)
Machine Learning The Ultimate Beginners Guide For Neural Networks, Algorithms, Random Forests and Decision Trees Made Simple
Neural Preprocessing and Control of Reactive Walking Machines: Towards Versatile Artificial Perception-Action Systems (Cognitive Technologies)
New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms (Studies in Computational Intelligence, 1146)
Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics (Studies in Computational Intelligence Book 1096)
Artificial Intelligence and Security Challenges in Emerging Networks
Deep Learning Demystified A Step-by-Step Introduction to Neural Networks
Artificial Intelligence in Higher Education and Scientific Research: Future Development (Bridging Human and Machine: Future Education with Intelligence)
Power Converters and AC Electrical Drives with Linear Neural Networks (Energy, Power Electronics, and Machines)
Neural Networks and Animal Behavior (Monographs in Behavior and Ecology, 29)
Build Your Own Neural Networks Step-By-Step Explanation For Beginners
Quantum Machine Learning Quantum Algorithms and Neural Networks
Quantum Machine Learning Quantum Algorithms and Neural Networks
Hands-On Convolutional Neural Networks with TensorFlow: Solve computer vision problems with modeling in TensorFlow and Python
Learning Deep Learning Theory and Practice of Neural Networks, Computer Vision, NLP, and Transformers using TensorFlow
Beginning Mathematica and Wolfram for Data Science: Applications in Data Analysis, Machine Learning, and Neural Networks
Python Deep Learning: Understand how deep neural networks work and apply them to real-world tasks
Artificial Intelligence in Wireless Sensors and Instruments Networks and Applications
Artificial Intelligence in Wireless Sensors and Instruments Networks and Applications
Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems
Python Machine Learning For Beginners An introduction to neural networks and a brief overview of the processes you need to know when programming computers and coding with Python
Learning Deep Learning Theory and Practice of Neural Networks, Computer Vision, NLP, and Transformers using TensorFlow (Rough Cuts)
Artificial Intelligence How it Changes the Future
Future of Networks Modern Communication Infrastructure
Networks of the Future Architectures, Technologies, and Implementations
Deep Learning and Convolutional Neural Networks for Medical Image Computing: Precision Medicine, High Performance and Large-Scale Datasets (Advances in Computer Vision and Pattern Recognition)
Federated Learning for Future Intelligent Wireless Networks
Federated Learning for Future Intelligent Wireless Networks
Federated Learning for Future Intelligent Wireless Networks
Artificial Intelligence What Is Behind the Technology of the Future?