Results 71 to 80 of about 1,188,978 (260)

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

Advanced Intelligent Discovery, EarlyView.
Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung, Seongmin Kim, Jaehyun Park, Chaeyoung Park, Zhihao Xu, Sanghyo Hwang, Baiqing Ye, Youn sang Kim, Sun‐Kyung Kim, Tengfei Luo, Eungkyu Lee   +10 more
wiley   +1 more source

A Meta-Heuristic Algorithm-Based Feature Selection Approach to Improve Prediction Success for Salmonella Occurrence in Agricultural Waters

Journal of Agricultural Sciences
The presence of Salmonella in agricultural waters may be a source of produce contamination. Recently, the performances of various algorithms have been tested for the prediction of indicator bacteria population and pathogen occurrence in agricultural ...
Murat Canayaz, Murat Demir, Zeynal Topalcengiz   +2 more
doaj   +1 more source

A Two‐Stage Characterization Pipeline and Open‐Source Framework for Reproducible Tactile Sensing

Advanced Intelligent Systems, EarlyView.
The same soft tactile sensor returns different numbers when embodied in different robots. This is an Embodiment Gap that no shared framework currently captures transparently. A two‐stage characterization pipeline, paired with a FAIR open‐source digital datasheet, decouples intrinsic sensor behavior from embodiment effects and condenses cross‐laboratory
Matteo Lo Preti, Weng Buxiu, Petr Trunin, Muhammad Sunny Nazeer, Lucia Beccai, Perla Maiolino, Cecilia Laschi   +6 more
wiley   +1 more source

A Virtual Machine Consolidation Algorithm Based on Ant Colony System and Extreme Learning Machine for Cloud Data Center

IEEE Access, 2020
The energy consumption issue of large-scale data centers is attracting more and more attention. Virtual machine consolidation can significantly reduce energy consumption by migrating virtual machines from one physical machine to another.
Fagui Liu, Zhenjiang Ma, Bin Wang, Weiwei Lin   +3 more
doaj   +1 more source

USULAN KESEIMBANGAN LINTASAN PRODUKSI DI LINE MAIN ASSY GAGA DENGAN METODE KILLBRIDGE-WESTER HEURISTIC UNTUK MENINGKATKAN EFESENSI DAN PRODUKTIVITAS KERJA [PDF]

Keseimbangan lini adalah suatu penugasan sejumlah pekerjaan kedalam stasiun-stasiun kerja yang saling berkaitan dalam suatu lintasan atau lini produksi dengan tujuan meminimumkan waktu menganggur pada lintasan yang telah ditentukan oleh operasi yang ...
Subakti, Arif, Rivandi, Merdieco
core   +1 more source

A NEAT Approach to Evolving Neural‐Network‐Based Optimization of Chiral Photonic Metasurfaces: Application of a NeuroEvolution‐of‐Augmenting‐Topologies Pipeline

Advanced Intelligent Systems, EarlyView.
Neuro‐evolution can boost machine‐learning optimization of chiral metasurfaces. By integrating the NEAT algorithm into a deep‐learning framework, we enable the efficient design of visible‐spectrum chiroptical responses. NEAT autonomously evolves neural‐network architectures and weights, reducing manual tuning.
Davide Filippozzi, Arash Rahimi‐Iman
wiley   +1 more source

Resilient Multimodal Fusion for Robust Vulnerability Exploitability Prediction Under Data Degradation

Advanced Intelligent Systems, EarlyView.
Secure Fusion‐X harmonizes unstructured NVD descriptions with structured CVSS/CWE/CPE metadata via decision‐level fusion, overcoming the fragility of traditional unimodal models. Automated assessment of software vulnerability exploitability is essential for intelligent cyber defense, yet its effectiveness is often hindered by unstable, delayed, or ...
Mona Dolati, Seyedeh Leili Mirtaheri, Reza Shahbazian, Andrea Pugliese   +3 more
wiley   +1 more source

Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018–2023)

Energy Strategy Reviews
The synergy between deep learning and meta-heuristic algorithms presents a promising avenue for tackling the complexities of energy-related modeling and forecasting tasks.
Eghbal Hosseini, Abbas M. Al-Ghaili, Dler Hussein Kadir, Saraswathy Shamini Gunasekaran, Ali Najah Ahmed, Norziana Jamil, Muhammet Deveci, Rina Azlin Razali   +7 more
doaj   +1 more source

Application of predator-prey optimization for task scheduling in cloud computing [PDF]

Journal of Mahani Mathematical Research
Cloud computing environments require scheduling to allocate resources efficiently and ensure optimal performance. It is possible to maximize resource utilization and minimize execution time by scheduling cloud systems effectively.
Zahra Jalali Khalil Abadi, Behnam Mohammad Hasani zade, Najme Mansouri, Mohammad Masoud Javidi   +3 more
doaj   +1 more source

Choice experiments on land managers' participation in environmental programs: A systematic review and meta‐analysis of estimate validity

American Journal of Agricultural Economics, EarlyView.
Abstract Discrete choice experiments are increasingly being used to estimate land managers' willingness to accept participation in incentive‐based environmental programs. This is a specific application of discrete choice experiments: the estimation of willingness to accept for a private good (program participation) where respondents have to make trade ...
Anastasio J. Villanueva, Angel Perni, Jesus Barreiro‐Hurle   +2 more
wiley   +1 more source