503 hasil untuk machine learning
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Multivariate Statistical Machine Learning Methods for Genomic Prediction
…an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for…
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Machine Learning and Its Application to Reacting Flows
This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows. These two fields, ML and turbulent combustion, have large…
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Machine learning aided multiscale mechanics of fiber suspensions
…with the FFT-based computational approach by leveraging supervised machine learning techniques. Furthermore, we present a novel Deep Material Network architecture capable of treating suspensions of rigid particles with high computational efficiency.
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Machine Learning im Cost Engineering des Supply Managements
…die einen Cost Engineer bei seinen Kostenschätzungen mithilfe von Machine Learning (ML) zielgerichtet unterstützen. Durch das experimentelle Design und eine Vielzahl von Testergebnissen gelingt es, Best Practices von ML-Modellen für die Kostenprognose von zu beschaffenden Bauteilen und Baugruppen…
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Chapter Machine Learning-Based Construction Planning and Forecasting Model
Construction planning and scheduling are crucial aspects of project management that require a lot of time and resources to manage effectively. Machine learning and artificial intelligence techniques have shown great potential in improving construction planning and scheduling by providing more…
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Foundations and Advances of Machine Learning in Official Statistics
This Open access book gives an overview of current research and developments on the incorporation of machine learning in official statistics. It covers methodological questions, practical aspects and cross-cutting issues. Machine learning has become an integral part of official statistics over the…
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Energy Efficiency and Robustness of Advanced Machine Learning Architectures
Machine Learning (ML) algorithms have shown a high level of accuracy, and applications are widely used in many systems and platforms. However, developing efficient ML-based systems requires addressing three problems: energy-efficiency, robustness, and techniques that typically focus on optimizing…
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Cyclic motion analysis using inertial sensors and machine learning
…cyclic motion using inertial sensors and subsequently analyse them using machine learning techniques. A lack of realistic and annotated data currently limits the development and application of algorithms for inertial sensors under non-laboratory conditions. This is due to the effort required to…
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Machine Learning for Camera-Based Monitoring of Laser Welding Processes
…and post-process monitoring of welding processes. The implementation uses machine learning methods. All algorithms consider the integration into industrial processes. These challenges include a small database, limited industrial manufacturing inference hardware, and user acceptance.
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Predicting Inequality of Opportunity and Poverty in India Using Machine Learning
This open-access book combines traditional economic methods with newer machine learning techniques such as regression trees and random forests to analyse data and provide an in-depth analysis of inequality of opportunity and poverty in India. Using data from national surveys and unique sources like…
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Chapter Citizen science and machine learning forecasting Ostreopsis cf ovata blooms
…a citizens’ observatory engaged with public research centres to apply a machine learning approach and develop a predictive modelling tool able to forecast O. ovata blooms. We applied the Quantile Regression Forest to draw up two models named Model4Cities and Citizens’Model. Model4Cities was trained…
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Development of a modular Knowledge-Discovery Framework based on Machine Learning
In this work, a novel knowledge discovery framework able to analyze data produced in the Gasoline Direct Injection (GDI) context through machine learning is presented and validated. This approach is able to explore and exploit the investigated design spaces based on a limited number of…
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Artificial Intelligence and Machine Learning in Health Care and Medical Sciences
This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a…
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Chapter Machine learning for sustainable land management: A focus on Italy
Soil salinization poses a multifaceted challenge demanding a comprehensive approach combining environmental science, machine learning, geography, and socio- economic analysis. Our study integrates these disciplines to unravel the complexities of soil salinization and devise effective mitigation…
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Chapter AI and Machine Learning to extend Meteo-Marine Station Observations into the Future
…and decision-making processes. This study explores the application of Machine Learning (ML) techniques to predict hourly values of air temperature, wind speed, atmospheric pressure, and humidity for the next 24 hours. We evaluate three ML models: Long Short-Term Memory Network (LSTM), Random Forest…
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Machine Learning im Logistikmanagement – Entwicklung eines Gestaltungsansatzes zum Einsatz von ML-Anwendungen in logistischen Entscheidungsprozessen
As a subfield of artificial intelligence, machine learning (ML) represents a key technology of the 21st century. Using the mathematical-statistical methods, technical systems can be developed that independently discover empirical patterns on the basis of data and thus adapt their behavior to solve…
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Chapter Il machine learning in ambito medico sanitario: il riconoscimento delle immagini e degli spazi
The here collected contributions relating to the 46th International Conference of the Representation Disciplines Teachers, organized jointly by Sapienza University of Rome, Roma Tre University, and San Raffaele Roma University, aim to offer the scientific community a reflection on the theoretical…
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Chapter Machine Learning Techniques to Mitigate Nonlinear Phase Noise in Moderate Baud Rate Optical Communication Systems
…between the optical carrier and the transmitted radio frequency signal. Machine learning algorithms have become a powerful tool to perform monitoring and to identify and mitigate distortions introduced in both the electrical and optical domains. Clustering-based demodulation assisted with Voronoi…
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Application of Data Mining and Machine Learning Methods to Industrial Heat Treatment Processes for Hardness Prediction
…assessment for preprocessing, feature extraction, and drift corrections. Machine learning is employed to devise robust prediction strategies for hardness. Its implementation in an industry pilot demonstrates the economic benefits of the framework.
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Machine learning and hyper spectral imaging: multi spectral endoscopy in the gastro intestinal tract towards hyper spectral endoscopy
Worldwide, carcinomas are the second leading cause of death after cardiovascular diseases. Of these, more than 25 % are caused by cancer in the gastrointestinal tract. However, screening still misses about 20 % of carcinomas. An optimal solution would be a red flag technology to locate the…