Lamarti Sefian / Khaldi | Mathematics Artificial Intelligence and Its Applications (MAIA) | Buch | 978-3-032-41623-0 | www.sack.de

Buch, Englisch, 280 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Networks and Systems

Lamarti Sefian / Khaldi

Mathematics Artificial Intelligence and Its Applications (MAIA)


Erscheinungsjahr 2027
ISBN: 978-3-032-41623-0
Verlag: Springer

Buch, Englisch, 280 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Networks and Systems

ISBN: 978-3-032-41623-0
Verlag: Springer


This book revises and updates the GEM Guidelines developed about a decade ago by the Good Experimental Methodology and Benchmarking EURON Special Interest Group. Implementing and publishing research advances across all disciplines are pressing issues in robotics and AI/cognition. As such, there is a need for reproducible findings, performance evaluation, and comparison of the various approaches. This book offers general review guidelines as well as specialist guidelines for a number of broad subareas. It provides a solid starting point and much needed reference resource for researchers wanting to make their work reproducible, or simply put, to give their work a sound scientific value. It is intended for researchers and practitioners from academia and industry, as well as those involved in research, innovation and publishing in robotics and AI/cognition.

Lamarti Sefian / Khaldi Mathematics Artificial Intelligence and Its Applications (MAIA) jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


A Hybrid Framework for Enhancing AI Risk Management in Banking Systems.- A Comparative Study of Statistical and Deep Learning Models for Stock Price Time Series Forecasting: Evidence from the Casablanca Stock Exchange (ADH Case Study).- From Stochastic Parrots to Pedagogical Partners: A Conceptual Framework for Designing Trustworthy AI in Instructional Engineering.- Toward Adaptive Knowledge Assessment in E-Learning Environments: A Literature Review (2020–2024).- Scenario-Based Approach Applied to a Probabilistic Support Vector Machine.- Perceptions, Uses, and Challenges Related to Artificial Intelligence among Moroccan University Students: An Exploratory Study.- Data-Driven Prediction of Electricity Distribution Incidents Using a Hybrid Learning Framework: Evidence from Northern Morocco.- Validation of the Attitudes Toward Mathematics Inventory (ATMI) in the Moroccan Context.- Crisis-Driven Dynamics of Cryptocurrency and Foreign Exchange Markets: Evidence from Machine and Deep Learning Models.- Intelligent Approach for a Recommendation System of Pedagogical Resources in Adaptive E-Learning.- Quarterly GDP Forecasting in Morocco Using Hybrid Generative and Predictive Models.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.