Data-Driven Evolutionary Optimization: Integrating Evolutionary Computation, Machine Learning and Data Science
Jun 2021 · Springer Nature
eBook
393
Halaman
reportRating dan ulasan tidak diverifikasi Pelajari Lebih Lanjut
Tentang eBook ini
Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available.
This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included.
Beri rating eBook ini
Sampaikan pendapat Anda.
Informasi bacaan
Smartphone dan tablet
Instal aplikasi Google Play Buku untuk Android dan iPad/iPhone. Aplikasi akan disinkronkan secara otomatis dengan akun Anda dan dapat diakses secara online maupun offline di mana saja.
Laptop dan komputer
Anda dapat mendengarkan buku audio yang dibeli di Google Play menggunakan browser web komputer.
eReader dan perangkat lainnya
Untuk membaca di perangkat e-ink seperti Kobo eReaders, Anda perlu mendownload file dan mentransfernya ke perangkat Anda. Ikuti petunjuk Pusat bantuan yang mendetail untuk mentransfer file ke eReaders yang didukung.
