Free Download Numerical Modeling: Prediction of Ship Maneuvering and Hydrodynamics During Inland Waterway Transport
by Peng Du, Haibao Hu
English | 2022 | ISBN: 168507278X | 194 Pages | PDF | 11 MB

Free Download Musculoskeletal Pain – Assessment, Prediction and Treatment
English | 2020 | ISBN: 191208550X | 213 Pages | PDF EPUB (True) | 46 MB
Musculoskeletal Pain – Assessment, Prediction and Treatment presents a common sense approach to interpreting and applying existing clinical knowledge and new research to help clinicians make sense of the complex phenomena of acute and chronic post-traumatic musculoskeletal pain. Built upon the Assess, Predict, Treat framework, the authors offer a method to help clinicians better understand their patients’ pain. They present evidence-based decision tools to predict the natural and clinical course of common conditions, such as neck and low back pain, and they then synthesize that information into a logical, integrated treatment approach, which respects the individuality of the patient, the experiences of the clinician, and the value of evidence-informed practice.

Free Download Generative AI with Heart Attack Prediction Kaggle Project

Published: 12/2024
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 23h 9m | Size: 8.48 GB
Master in Data Science and Use Gen AI tools to predict heart attacks using Kaggle datasets and ChatGPT-4o’s super power

Free Download Default Loan Prediction Based On Customer Behavior
Using Machine Learning And Deep Learning With Python
English | 2022 | ASIN : B09S3CC7SK | 334 Pages | PDF | 12 MB

Free Download Trust-based Collective View Prediction By Tiejian Luo, Su Chen, Guandong Xu, Jia Zhou (auth.)
2013 | 146 Pages | ISBN: 1461472016 | PDF | 4 MB
Collective view prediction is to judge the opinions of an active web user based on unknown elements by referring to the collective mind of the whole community. Content-based recommendation and collaborative filtering are two mainstream collective view prediction techniques. They generate predictions by analyzing the text features of the target object or the similarity of users’ past behaviors. Still, these techniques are vulnerable to the artificially-injected noise data, because they are not able to judge the reliability and credibility of the information sources. Trust-based Collective View Prediction describes new approaches for tackling this problem by utilizing users’ trust relationships from the perspectives of fundamental theory, trust-based collective view prediction algorithms and real case studies. The book consists of two main parts – a theoretical foundation and an algorithmic study. The first part will review several basic concepts and methods related to collective view prediction, such as state-of-the-art recommender systems, sentimental analysis, collective view, trust management, the Relationship of Collective View and Trustworthy, and trust in collective view prediction. In the second part, the authors present their models and algorithms based on a quantitative analysis of more than 300 thousand users’ data from popular product-reviewing websites. They also introduce two new trust-based prediction algorithms, one collaborative algorithm based on the second-order Markov random walk model, and one Bayesian fitting model for combining multiple predictors. The discussed concepts, developed algorithms, empirical results, evaluation methodologies and the robust analysis framework described in Trust-based Collective View Prediction will not only provide valuable insights and findings to related research communities and peers, but also showcase the great potential to encourage industries and business partners to integrate these techniques into new applications.

Free Download Prediction of Protein Secondary Structure, 2nd Edition
by Andrzej Kloczkowski, Lukasz Kurgan
English | 2025 | ISBN: 1071641956 | 360 Pages | True PDF | 23.6 MB

Free Download ROC Analysis for Classification and Prediction in Practice
English | 2023 | ISBN: 1482233703 | 234 Pages | PDF EPUB (True) | 13 MB
This book presents a unified and up-to-date introduction to ROC methodologies, covering both diagnosis (classification) and prediction. The emphasis is on the conceptual underpinning of ROC analysis and the practical implementation in diverse scientific fields. A plethora of examples accompany the methodologic discussion using standard statistical software such as R and STATA. The book arrives after two decades of intensive growth in both the methods and the applications of ROC analysis and presents a new synthesis. The authors provide a contemporary, integrated exposition of ROC methodology for both classification and prediction and include material on multiple-class ROC. This book avoids lengthy technical exposition and provides code and datasets in each chapter. ROC Analysis for Classification and Prediction in Practice is intended for researchers and graduate students, but will also be useful for those that use ROC analysis in diverse disciplines such as diagnostic medicine, bioinformatics, medical physics, and perception psychology.

Free Download Nostradamus 2013: Prediction, Modeling and Analysis of Complex Systems By Guanrong Chen (auth.), Ivan Zelinka, Guanrong Chen, Otto E. Rössler, Vaclav Snasel, Ajith Abraham (eds.)
2013 | 529 Pages | ISBN: 3319005413 | PDF | 22 MB
Prediction of behavior of the dynamical systems, analysis and modeling of its structure is vitally important problem in engineering, economy and science today. Examples of such systems can be seenin the world around us and of course in almost every scientific discipline including such "exotic" domains like the earth’s atmosphere, turbulent fluids, economies (exchange rate and stock markets),population growth, physics (control of plasma), information flow in social networks and its dynamics, chemistry and complex networks. To understand such dynamics and to use it in research or industrialapplications, it is important to create its models. For this purpose there is rich spectra of methods, from classical like ARMA models or Box Jenkins method to such modern ones like evolutionarycomputation, neural networks, fuzzy logic, fractal geometry, deterministic chaos and more. This proceeding book is a collection of the accepted papers to conference Nostradamus that has been held in Ostrava, Czech Republic. Proceeding also comprises of outstanding keynote speeches by distinguished guest speakers: Guanrong Chen (Hong Kong), Miguel A. F. Sanjuan (Spain), Gennady Leonov and Nikolay Kuznetsov (Russia), Petr ?koda (Czech Republic).The main aim of the conference is to create periodical possibility for students, academics and researchers to exchange their ideas and novel methods. This conference will establish forum forpresentation and discussion of recent trends in the area of applications of various predictive methods for researchers, students and academics.

Free Download Early Software Reliability Prediction: A Fuzzy Logic Approach By Ajeet Kumar Pandey, Neeraj Kumar Goyal (auth.)
2013 | 153 Pages | ISBN: 8132211758 | PDF | 4 MB
The development of software system with acceptable level of reliability and quality within available time frame and budget becomes a challenging objective. This objective could be achieved to some extent through early prediction of number of faults present in the software, which reduces the cost of development as it provides an opportunity to make early corrections during development process. The book presents an early software reliability prediction model that will help to grow the reliability of the software systems by monitoring it in each development phase, i.e. from requirement phase to testing phase. Different approaches are discussed in this book to tackle this challenging issue. An important approach presented in this book is a model to classify the modules into two categories (a) fault-prone and (b) not fault-prone. The methods presented in this book for assessing expected number of faults present in the software, assessing expected number of faults present at the end of each phase and classification of software modules in fault-prone or no fault-prone category are easy to understand, develop and use for any practitioner. The practitioners are expected to gain more information about their development process and product reliability, which can help to optimize the resources used.

Free Download Clustering, Classification, and Time Series Prediction by Using Artificial Neural Networks by Patricia Melin , Martha Ramirez , Oscar Castillo
English | PDF EPUB (True) | 2024 | 82 Pages | ISBN : 3031711009 | 9.5 MB
This book provides a new model for clustering, classification, and time series prediction by using artificial neural networks to computationally simulate the behavior of the cognitive functions of the brain is presented. This model focuses on the study of intelligent hybrid neural systems and their use in time series analysis and decision support systems. Therefore, through the development of eight case studies, multiple time series related to the following problems are analyzed: traffic accidents, air quality and multiple global indicators (energy consumption, birth rate, mortality rate, population growth, inflation, unemployment, sustainable development, and quality of life). The main contribution consists of a Generalized Type-2 fuzzy integration of multiple indicators (time series) using both supervised and unsupervised neural networks and a set of Type-1, Interval Type-2, and Generalized Type-2 fuzzy systems. The obtained results show the advantages of the proposed model of Generalized Type-2 fuzzy integration of multiple time series attributes. This book is intended to be a reference for scientists and engineers interested in applying type-2 fuzzy logic techniques for solving problems in classification and prediction. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the book.