Text

Deep neuro-fuzzy systems with python: with case studies and applications from the industry 1st ed. Edition, kindle edition

---

Gain insight into fuzzy logic and neural networks, and how the integration between the two models makes intelligent systems in the current world. This book simplifies the implementation of fuzzy logic and neural network concepts using Python.



You’ll start by walking through the basics of fuzzy sets and relations, and how each member of the set has its own membership function values. You’ll also look at different architectures and models that have been developed, and how rules and reasoning have been defined to make the architectures possible. The book then provides a closer look at neural networks and related architectures, focusing on the various issues neural networks may encounter during training, and how different optimization methods can help you resolve them.



In the last section of the book you’ll examine the integrations of fuzzy logics and neural networks, the adaptive neuro fuzzy Inference systems, and various approximations related to the same. You’ll review different types of deep neuro fuzzy classifiers, fuzzy neurons, and the adaptive learning capability of the neural networks. The book concludes by reviewing advanced neuro fuzzy models and applications.

---

Ketersediaan

Informasi Detail

Judul Seri

-

No. Panggil

005.133 SIN d

Penerbit

India : apress., 2019

Deskripsi Fisik

278halaman.; 26cm

Bahasa

English

ISBN/ISSN

978-1484253601

Klasifikasi

005.133

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

Edisi satu, November 2019

Subjek

-

Info Detail Spesifik

-

Pernyataan Tanggungjawab

Himanshu Singh.; Yunis Ahmad Lone

Versi lain/terkait

Lampiran Berkas

Komentar

---

Anda harus masuk sebelum memberikan komentar