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This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selecta

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Hoher Kontrast zwischen Text und Hintergrundfarbe

Strukturelle Navigation Nächste/Zurück

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Springer Proceedings in Mathematics & Statistics

Dieky Adzkiya

Kistosil Fahim

Applied and Computational Mathematics

ICoMPAC 2023, Sukolilo, Indonesia, September 30

&lt;p&gt;Part 1: Applied Mathematics (Control Systems, Mathematical Simulation, and Modeling).- H. Margaretha, N. Satyahadi and F. V. Ferdinand, Simulation of Investment Behaviors using Risk-Influenced Utility Models of Health and Wealth.- R. K. Dewi, I. Magdalena and I. Marcela, Wave Attenuation by a Combination of Mangroves and Reefball.- R. M. Valerio and I. Magdalena, Resonance Detection in a Semi-Closed Basin with Constant Height and Triangular Width.- R. Rahmawati, L. Harsyiah and Z. W. Baskara, Comparison of Ridge Regression and Principal Component Regression in Overcoming Multicolinierity of Factors Affecting Poverty in Indonesia.- Ahmadin, J. Naiborhu, Fatmawati and Windarto, Identification on Class Nonlinear Control System with Relative Degree Two.- A. F. Khariri, P. K. Intan, Moh. Hafiyusholeh, A. H. Asyhar and A. Fanani, Implementation of K-Means Particle Swarm Optimisation for Clustering Football Players in The Top Five European Football Leagues.- M. Widianto, C. Imron and B. Widodo, A short review of numerical modelling for photocatalytic degradation in dye systems.- S. Subchan, H. Purnawan, T. Asfihani and L. R. Amalia, Reference Tracking of Quadrotor using Modified Nonlinear Model Predictive Control based on Nonlinear Disturbance Observer.- D. Savitri, M. Jakfar and L. Putri, Numerical Simulation and Dynamics of Sedimentation Rate with Seagrass Growth Considering Dredging Factors.- H. Nuha, N. Siswanto and E. Widodo, A Mixed Integer Nonlinear Programming for Allocation Polyethylene Terephthalate (PET) Waste Management in Reverse Logistic Network.- A. Zaki Al Muntazhar, D. Ratna Sulistyaningrum and Subiono, Quantum K-Nearest Neighbors For Object Recognition.- T. Asfihani, F. N. Sihan Novita Lutfiani, A. Maulana Syafi'I, Subchan Subchan and A. Hasan, Adaptive Kalman Filter for Automated Actuator Fault Diagnosis in Unmanned Surface Vehicle.- E. R M Putri, A. Wahyu Widianto, A. Hakam, V. Ryan Tjahjono and H. Susanto, A moving average genetic algorithm (MA-GA)for estimating the COVID-19 dynamic based on a stochastic SIRD model.- A. Hakam, E. R M Putri and L. Mardiyanto, A general solution of Black-Scholes equations on some Rainbow options.- F. Ardhiansyah, R. W. Prastianto, M. Murdjito, K. Suastika and S. Nugroho, Dynamic Response of Floating Crane During Lifting Operation: A Parametric Study.- Part 2: Computational Mathematics (Formal Methods and Data Science): M. T. Ammar, M. Arzaki and G. S. Wulandari, Efficient SAT-Based Approach for Solving Juosan Puzzles.- J. E. Sakti, M. Arzaki and G. S. Wulandari, Modeling Path Puzzles as SAT Problems and How to Solve Them.- H. Tanabe and M. Kimura, A trustworthiness scoring model for reviews using a graph structure.- M. Iqbal, A. Afandy and N. Hidayat, Non-Linear Reward Deep Q Networks for Smooth Action in A Car Game.- Arthur de Clairval, L. A. Erwin Schuler, M. F. Rellier, M. Isa Irawan, I. Mukhlash and M. Iqbal, College Student Activity Recognition from Smartwatch Dataset.- A. Taryana, D. Adzkiya, M. Syifa'ul Mufid, I. Mukhlash and A. Abate, LTL Model Checking for Verification of Electronic Medical Record (EMR) Design.- G. I. Permata Sari, Hsing-Kuo Pao, R. C. Hario Pribadi and M. Iqbal, Multi-Feature Subgraph Fusion with Text Knowledge on Citation Link Prediction.- I Komang Pande Prajadhita Wibawa Putra, I. Irhamah, Nur Iriawan and K. Fithriasari, Predicting Poverty Percentage Based on Satellite Imagery and Point of Interest Using Support Vector Regression and Random Forest Regression (Case Study of Central Java Province).- M. Hutapea, G. Wulandari and M. Arzaki, Preliminary Analysis of Isabelle Proof Assistant in Graph Programming Verification with GP2.- Part 3: Pure Mathematics (Graph Theory and Analysis): T. Irvan Haryadi, R. Rinurwati, D. Winda Setyawati, S. Soleha, I. Herisman, K. Baihaqi and S. Sadjidon, Nonlocal Edge Metric Dimension on Corona Multiproduct Graphs.- N. Ain Supu, I. M. Alamsyah and E. Suwastika, The Vertex Degree of Relative g-noncommuting Graph of the Dihedral Groups.- S. Wibowo and C. R. Indrati, On Conformable Fractional Riesz Bounded p-Variation of Order- α.- H. K. Ningrum, E. Y. Asmarani, I Gede Adhitya Wisnu Wardhana, S. Salwa and Z. Y. Awanis, The Wiener Index, The Harmonic Index, and The Graph Representation of the Prime Ideal Graph for the Integers Modulo Rings with Prime Power Order.- R. Rinurwati, M. Chalid Fansury, A. Hevita G.K. Saefulloh and T. I. Haryadi, Multiplicative Sum Nano Zagreb Index of Various 2-Power Corona Graphs.&lt;br&gt;&lt;/p&gt;

Six Dimensions of Business Dark Data

Agentic Hyper-Personalized Dimensions

Concepts, Models, and Applications

Learning-Driven Game Theory for AI

Retrieval-Augmented Generation (RAG) represents the cutting edge of AI innovation, bridging the gap between large language models (LLMs) and real-world knowledge. This book provides the definitive roadmap for building, optimizing, and deploying enterprise-grade RAG systems that deliver measurable business value.This comprehensive guide takes you beyond basic concepts to advanced implementation strategies, covering everything from architectural patterns to production deployment. You'll explore proven techniques for document processing, vector optimization, retrieval enhancement, and system scaling, supported by real-world case studies from leading organizations.Key Learning Objectives<ul><li>Design and implement production-ready RAG architectures for diverse enterprise use cases</li><li>Master advanced retrieval strategies including graph-based approaches and agentic systems</li><li>Optimize performance through sophisticated chunking, embedding, and vector database techniques</li><li>Navigate the integration of RAG with modern LLMs and generative AI frameworks</li><li>Implement robust evaluation frameworks and quality assurance processes</li><li>Deploy scalable solutions with proper security, privacy, and governance controls</li></ul>Real-World Applications<ul><li>Intelligent document analysis and knowledge extraction</li><li>Code generation and technical documentation systems</li><li>Customer support automation and decision support tools</li><li>Regulatory compliance and risk management solutions</li></ul>Whether you're an AI engineer scaling existing systems or a technical leader planning next-generation capabilities, this book provides the expertise needed to succeed in the rapidly evolving landscape of enterprise AI.What You Will Learn<ul><li>Architecture Mastery: Design scalable RAG systems from prototype to enterprise production</li><li>Advanced Retrieval: Implement sophisticated strategies, including graph-based and multi-modal approaches</li><li>Performance Optimization: Fine-tune embedding models, vector databases, and retrieval algorithms for maximum efficiency</li><li>LLM Integration: Seamlessly combine RAG with state-of-the-art language models and generative AI frameworks</li><li>Production Excellence: Deploy robust systems with monitoring, evaluation, and continuous improvement processes</li><li>Industry Applications: Apply RAG solutions across diverse sectors, including finance, healthcare, legal, and technology</li></ul>

Advanced Techniques and Production-Ready Solutions for Enterprise AI

Mastering Retrieval-Augmented Generation

Encyclopedia of Optimization

Learn how to manage the risks and opportunities of agentic AI with this practical guide to ensuring the safe and beneficial developments of advanced AI systems.

Principles and Responsible Practices

Safer Agentic AI

This book is the first one that shows how to accurately and efficiently solve time-varying problems in real-time or online using continuous- or discrete-time zeroing dynamics. The authors provide a comprehensive treatment of the theory of both static and dynamic neural networks. They develop, analyze, model, simulate, and compare zeroing dynamics models for the online solution of numerous time-varying problems, such as root finding, nonlinear equation solving, matrix inversion, matrix square root finding, quadratic optimization, and inequality solving.

Zeroing Dynamics, Gradient Dynamics, and Newton Iterations

De Gruyter Studium

Algorithmen und Datenstrukturen

Modern Trends In Financial Engineering

Multiscale Financial Data Analytics and Machine Learning offers a systematic and comprehensive study on the multiscale approach to financial data analytics and machine learning. This book covers an array of multiscale methods to discover the properties of various timescales embedded in a financial time series, including noise-assisted empirical mode decomposition methods. Important interpretable multiscale outputs from the estimation are recognized as a new set of features that can be used for machine learning. The feature selection problem for machine learning is examined in this volume.This book offers an applied quantitative approach that combines novel analytical methodologies and practical applications to a wide array of examples with real-world data. It is self-contained and organized in its presentation. The explanations of the methodologies are both accessible and detailed enough to capture the interest of the curious student or researcher. Step-by-step descriptions of the algorithms are provided for straightforward implementation.

Multiscale Financial Data Analytics And Machine Learning

Troubleshoot and Optimize Query Performance

SQL Server 2025 Query Performance Tuning

Understanding China

This book sorts out the causes, consequences and the evolution path of China's economic reform process from the historical dimension of China's economic policy changes, from which the long-standing contradictions and conflicts between the two different models can be seen throughout the process, i.e. the market economy and the state-dominated economy (Lenin's 'special state capitalism') as well as the potential risks that will be brought by the pause of market and law reform on China's economic and social development. The dispute on the paths exists and will continue, which builds the great complexity and arduousness since China's Reform and Opening-up. This book is written by Chinese economist Jinglian Wu, which helps readers to understand the history and logic behind China's reform and opening-up, as well as the challenges China is facing.

China’s Economic Reform

Challenges and Applications of Generative Large Language Models

Key Technologies on New Energy Vehicles

This book focuses on the current advanced technology field of battery operation big data and comprehensively describes the frontier technology of big data analysis and intelligent control of battery safe operation. The content systematically introduces the coupling mechanism of battery system safety and consistency, battery SOH estimation and prediction, battery safety state prediction, battery fault diagnosis, battery system risk pre-warning, and safety control strategy research.This book is suitable for teachers and students of universities and colleges in the automotive and related industries, engineers and technicians in the R&amp;D departments of enterprises or automotive enthusiasts to read and refer.The basis of English translation of this book, originally in Chinese, was facilitated by artificial intelligence. The content was later revised by the author for accuracy.

Big Data Analysis and Application of Power Battery Operation Safety

Applied and Computational Mathematics

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