Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	Oktober 2025
Genre:	Wirtschaft / Recht
	BUSINESS & ECONOMICS / Industries / Manufacturing / BUSINESS & ECONOMICS / Production & Operations Management / BUSINESS & ECONOMICS / Quality Control / COMPUTERS / Data Science / Machine Learning / Manufacturing industries / Other vocational technologies & trades / Process engineering technology and techniques / Production & quality control management / Production and quality control management mehr...
ISBN:	9780443315640
EAN-Code:	9780443315640
Verlag:	Elsevier
Einband:	Kartoniert
Sprache:	English
Dimensionen:	H 229 mm / B 152 mm / D 19 mm
Gewicht:	570 gr
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

Small Sample Modelling Based on Deep and Broad Forest Regression: Theory and Industrial Application delves into tree-structured methods in the industrial sector, encompassing classical ensemble learning, tree-structured deep forest classification, and broad learning systems with neural networks. It introduces an innovative deep/broad learning algorithm for small-sample industrial modeling tasks. The book is divided into two parts: methodology and practical application in dioxin emission modeling. Methodology sections include Preliminaries, Deep Forest Regression, Broad Forest Regression, and Fuzzy Forest Regression. The application part focuses on modeling dioxin emissions in municipal solid waste incineration. Throughout, various tree-structured strategies are presented, and the authors provide software systems for validating these methods. This book is suitable for advanced undergraduates, graduate engineering students, and practicing engineers looking for self-study resources.