close
1.

電子ブック
ＥＢ
1. Black Box Optimization, Machine Learning, and No-Free Lunch Theorems. 1st ed. 2021
edited by Panos M. Pardalos, Varvara Rasskazova, Michael N. Vrahatis
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2021
シリーズ名: Springer Optimization and Its Applications ; 170
オンライン: https://doi.org/10.1007/978-3-030-66515-9
所蔵情報: loading…
目次情報: 続きを見る
Learning enabled constrained black box optimization (Archetti)
Black-box optimization: Methods and applications (Hasan)
Tuning algorithms for stochastic black-box optimization: State of the art and future perspectives (Bartz-Beielstein)
Quality diversity optimization: A novel branch of stochastic optimization (Chatzilygeroudis)
Multi-objective evolutionary algorithms: Past, present and future (Coello C.A)
Black-box and data driven computation (Du)
Mathematically rigorous global optimization and fuzzy optimization: A brief comparison of paradigms, methods, similarities and differences (Kearfott)
Optimization under Uncertainty Explains Empirical Success of Deep Learning Heuristics (Kreinovich)
Variable neighborhood programming as a tool of machine learning (Mladenovic)
Non-lattice covering and quanitization of high dimensional sets (Zhigljavsky)
Finding effective SAT partitionings via black-box optimization (Semenov)
The No Free Lunch Theorem: What are its main implications for the optimization practice? ( Serafino)
What is important about the No Free Lunch theorems? (Wolpert)
Learning enabled constrained black box optimization (Archetti)
Black-box optimization: Methods and applications (Hasan)
Tuning algorithms for stochastic black-box optimization: State of the art and future perspectives (Bartz-Beielstein)
2.

電子ブック
ＥＢ
2. Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities : Designing for Sustainability. 1st ed. 2022
edited by Panos M. Pardalos, Stamatina Th. Rassia, Arsenios Tsokas
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2022
シリーズ名: Springer Optimization and Its Applications ; 186
オンライン: https://doi.org/10.1007/978-3-030-84459-2
所蔵情報: loading…
目次情報: 続きを見る
Cities as Convergent Autopoietic Systems (V. Dobrev)
Digital ‘Vitalism’ and its ‘Epistemic’ Predecessors: ‘Smart’ Neoteric History and Contemporary Approaches (Moraitis)
Unbuildable Cities (Th. Rassia)
Smart Cities as Identities (Tsoniotis)
A Cross-domain Landscape of ICT Services in Smart Cities (Bunhova)
A Novel Data Representation Method for Smart Cities’ Big Data (N. Nagy)
A Pedestrian Level Strategy to Minimize Outdoor Sunlight Exposure (X. Li)
Planning and Management of Charging Facilities for Electric Vehicle Sharing (W. Qi)
A Reactive Architectural Proposal for Fog/edge Computing in the Internet of Things Paradigm with Application in Deep Learning (Belmonte-Fernandez)
Urban Big Data: City Management and Real Estate Markets (Saiz)
Social Media-based Intelligence for Disaster Response and Management in Smart Cities (Khatoon)
Cities as Convergent Autopoietic Systems (V. Dobrev)
Digital ‘Vitalism’ and its ‘Epistemic’ Predecessors: ‘Smart’ Neoteric History and Contemporary Approaches (Moraitis)
Unbuildable Cities (Th. Rassia)
3.

電子ブック
ＥＢ
3. Synthetic Aperture Radar (SAR) Data Applications. 1st ed. 2022
edited by Maciej Rysz, Arsenios Tsokas, Kathleen M. Dipple, Kaitlin L. Fair, Panos M. Pardalos
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2022
シリーズ名: Springer Optimization and Its Applications ; 199
オンライン: https://doi.org/10.1007/978-3-031-21225-3
所蔵情報: loading…
目次情報: 続きを見る
End-to-End ATR Leveraging Deep Learning (M. Kreucher)
Change Detection in SAR Images using Deep Learning Methods (Bovolo)
Homography Augmented Momentum Contrastive Learning for SAR Image Retrieval (M. Rysz)
Synthetic Aperture Radar Image Based Navigation Using Siamese Neural Networks (Semenov)
A Comparison of Deep Neural Network Architectures in Aircraft Detection from SAR Imagery (L. Chen)
Machine Learning Methods for SAR Interference Mitigation (Huang)
Classification of SAR Images using Compact Convolutional Neural Networks (Ahishali)
Multi-frequency Polarimetric SAR Data Analysis for Crop Type Classification using Random Forest (Mandal)
Automatic Determination of Different Soil Types via Several Machine Learning Algorithms Employing Radarsat-2 SAR Image Polarization Coefficients (E. Acar)
Ocean and coastal area information retrieval using SAR polarimetry (A. Buono)
End-to-End ATR Leveraging Deep Learning (M. Kreucher)
Change Detection in SAR Images using Deep Learning Methods (Bovolo)
Homography Augmented Momentum Contrastive Learning for SAR Image Retrieval (M. Rysz)