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Advances in Machine Learning and Big Data Analytics II de Ashokkumar Patel

Advances in Machine Learning and Big Data Analytics II: Springer Proceedings in Mathematics & Statistics, cartea 442

Editat de Ashokkumar Patel, Nishtha Kesswani, Bosubabu Sambana
en Limba Engleză Hardback – 27 sep 2025

În contextul programelor universitare actuale de masterat și doctorat în matematică aplicată și știința datelor, volumul Advances in Machine Learning and Big Data Analytics II reprezintă o resursă tehnică de actualitate, fiind fundamentat pe lucrările prezentate la conferința internațională ICMLBDA 2023. Notăm cu interes modul în care editorii Ashokkumar Patel, Nishtha Kesswani și Bosubabu Sambana au structurat această ediție 2024 pentru a reflecta convergența dintre algoritmii de învățare automată și complexitatea analizelor de tip Big Data.

Subliniem că acest volum extinde cadrul propus de Recent Developments in Machine Learning and Data Analytics de Jugal Kalita cu date noi și studii de caz din perioada 2023, punând un accent mai pronunțat pe implementările hardware și securitatea cloud. În ansamblul operei editorilor, lucrarea se poziționează ca o continuare firească a volumului Advances in Machine Learning and Big Data Analytics I, dar și ca un complement tehnic pentru Accelerating Discoveries in Data Science and Artificial Intelligence I, mutând focusul de la descoperirea teoretică spre validarea empirică în domenii critice.

Structura volumului este riguroasă, debutând cu analize statistice de precizie pentru imagistică medicală (RMN) și progresând spre soluții de securitate cibernetică, precum recunoașterea atacurilor web în IoT prin clasificare de ansamblu. Cuprinsul indică o acoperire transdisciplinară: de la utilizarea rețelelor neuronale convoluționale (CNN) și a modelului VGG-19 pentru identificarea speciilor de plante, până la optimizarea calității energiei prin filtre hibride active. Această ediție 2024 de la Springer oferă un ritm de expunere dens, specific lucrărilor de cercetare, unde fiecare capitol este susținut de date experimentale și modele matematice validate.

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Specificații

ISBN-13: 9783031513411
ISBN-10: 303151341X
Pagini: 396
Ilustrații: X, 470 p. 291 illus., 251 illus. in color.
Dimensiuni: 160 x 241 x 27 mm
Greutate: 0.76 kg
Ediția:2024
Editura: Springer
Colecția Springer Proceedings in Mathematics & Statistics
Seria Springer Proceedings in Mathematics & Statistics

Locul publicării:Cham, Switzerland

De ce să citești această carte

Recomandăm acest volum cercetătorilor și studenților avansați care doresc să înțeleagă aplicabilitatea imediată a învățării automate în scenarii reale de inginerie și medicină. Cititorul câștigă acces la metodologii de ultimă oră pentru procesarea seturilor mari de date și securizarea infrastructurilor cloud. Este un instrument esențial pentru cei care urmăresc tranziția de la teorie la prototipuri funcționale în inteligența artificială aplicată.

Descriere scurtă

In the dynamic landscape of technology, machine learning and big data analytics have emerged as transformative forces, reshaping industries and empowering innovation. Machine learning, a subset of artificial intelligence, equips systems to learn and adapt from data, revolutionizing decision-making, automation, and predictive capabilities. Meanwhile, Big Data Analytics processes and extracts insights from vast and complex datasets, unveiling hidden patterns and trends. Together, these fields enable us to harness the immense power of data for smarter business strategies, improved healthcare, enhanced user experiences, and countless other applications. This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2023, which was held on May 29-30, 2023 by NERIST and NIT Arunachal Pradesh India)  introduces an exciting journey into the intersection of machine learning and Big Data Analytics, where data becomes a catalyst for progress and transformation.

Cuprins

Precision Statistical Analysis of Denoising Algorithms used in MRI Images of Trans Ischemic Stroke.- Foreseeing Worker Attrition Using Machine Learning.- Comparative Analysis of Fuzzy Regular Graph Properties.- Design Analysis to Ascertain the Topological Structures Induced by Chromatic Partition of Vertex Set of Graphs.- Mouse Controlling Using Eyeball Action.- Effective Cloud Data Management by Using AES Encryption and Decryption.- Power Quality Improvement by Using Shunt Hybrid Active Power Filter.- Prediction of Angina Pectoris.- Multi layer CNN Model for Monkeypox Detection from Skin Images.- Integration of Renewable Energy Systems into utility grid: A review on Power Quality Issues, Mitigating devices and Control Algorithms.- A Novel Web Attack Recognition System for IoT via Ensemble Classification.- Automatic Identification of Medical Plant Species Using VGG-19 Model.- Identification of Fake Job Recruitment Using Several Machine Learning (ML) Models.- Identification of Customer Reviews and Ratings Using Natural Language Processing.- Fuzzy Programming Technique - A New Era to Define Membership Functions.- A Study on E-Commerce Enhanced Demographic Attributes Impact On Organic Food Products Using Setiment Analysis.- Traffic Control System for Congestion Control and Ambulance Clearance.- QR Based Authentication for Login and Payment.- Smart Irrigation Watering System Using IoT.- IoT Based Transmission Line Multiple Fault Detection and Indication to Electricity Board.- IoT-Based NPK Sensor System for Soil Nutrient Monitoring.- Design Of Off Board Electric Vehicle Charger Using PV Array Through Matlab-Simulink.- Smart Grid Power Quality Improvement Using Modified UPQC.- Human Stress Detection in Sleep Mode Compared with Non-Sleep Mode Using Machine Learning Algorithms.- A Survey on Novel Human Resource Management Practices Using Machine Learning.- Medical Diagnosis Prediction using Deep Learning.- SDS:Secure Image Transmission Using Advanced Encryption Standard With Salting, Steganography and Data Shredding Techniques.- Detecting Hard Landing of Flights: E-Pilots.- Detection of Glaucoma Using MobileNet, XAI and IML.- Multi Crop – Multi Disease Detection.- Avian Soundscape Analysis Using Machine Learning.- Smart Security and Surveillance System.- Cyber Money Laundering Detection Using Machine Learning Methods.- Attainment Expedients of Markovian Heterogeneous Water Heaters in Queueing Models by Matrix Geometry Method.- Accessible chatbot Interface for Price Negotiation System.- Identification Of Medicinal Plants Using Inception V3 Model.- Early Prediction Chronic Kidney Disease (CKD) from CT Images Using Deep Learning Model with Several Optimizers.- Smart Gardening Using Internet of Things.- Predictive Analytics of Blood Donor Risk Assessment Using Machine Learning Methods.- Risk Analysis of Covid-19 Patients Mortality Rate in Emergency Ward.- Recognizing and Logging Vehicles by Scanning License Plates and Driver’s Face.- Machine Learning Classification Analysis on Leaf Disease Data.- Machine learning based classification of X-ray images using Convolutional Neural Networks.- A Comparative Study of Inception Models for Bone X-rays Classification and Pathology Detection.- Conversion of Type-2 Intuitionistic Fuzzy Sets into Interval-valued Intuitionistic Fuzzy Sets and its implementation in Decision Making.- A Framework for Secure Database and Similarity Comparison in Android.- Dietary Assessment Report Generation using RCNN.- A Comprehensive Review and A Conceptual Framework for Predicting the Position of the Mobile Sinks in Wireless Sensor Networks.- Brain Computer Interface for Multiple Applications Control.- Predicting Student Academic Performance using Machine Learning: A Comparison of Classification Algorithms.- A Novel Approach in Machine Learning for Solar Energy Prediction System.- A Blockchain based Networking Approach for Advanced HealthCare Services.- Real-time Tomato Leaf Disease Detection and Diagnosis using Deep Learning-based Computer Vision Techniques.- Optimized Capacity and Scheduling Assessment for Li-Ion Battery in a Photovoltaic Enhanced Modern Distribution Grid on Reliability Enhancement Viewpoint.- Fine-grained Sentiment Analysis on Covid-19 Tweets using Deep Learning Techniques.- Index.

Caracteristici

Narrates the development of high-precision algorithms that makes more efficient technologies for healthcare Provides the advanced and conceptual reference materials that help in building and promoting ML and Big Data Provides future directions of R&D and real-world case studies for computer scientists, biomedical engineers