Results 131 to 140 of about 332,730 (283)

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

Biomarker‐Agnostic Detection of Ovarian Cancer from Blood Plasma Using a Machine Learning‐Driven Electronic Nose

Advanced Intelligent Systems, EarlyView.
This study introduces a biomarker‐agnostic diagnostic strategy for ovarian cancer, utilizing a machine learning‐enhanced electronic nose to analyze volatile organic compound signatures from blood plasma. By overcoming the dependence on specific biomarkers, this approach enables accurate detection, staging, and cancer type differentiation, offering a ...
Ivan Shtepliuk, Lingyin Meng, Christer Borgfeldt, Jens Eriksson, Donatella Puglisi   +4 more
wiley   +1 more source

Metalearning‐Driven Inverse Optimization for Precision Microstructure Fabrication in Digital Light Processing Three‐Dimensional Printing

Advanced Intelligent Systems, EarlyView.
Metalearning‐based inverse optimization enables precise microscale three‐dimensional printing using a DLP system. Distorted structures from conventional printing are analyzed via neural network regression, which predicts optimal exposure time and mask design.
Jae Won Choi, Suhyeong Lim, Jeongsu Lee, Cheol Woo Ha   +3 more
wiley   +1 more source

Minimizing makespan for mixed batch scheduling with identical machines and unequal ready times

Scientific Reports
This study addresses the problem of minimizing the makespan for scheduling parallel batch machines, where jobs are processed in batches and each machine has the same capacity.
JinDian Huang
doaj   +1 more source

Context‐Aware Semiautonomous Control for Upper‐Limb Prostheses

Advanced Intelligent Systems, EarlyView.
A semiautonomous prosthetic control strategy integrates electromyographic‐based intention with computer vision‐driven grasp adaptation and wrist orientation. Comparative experiments with functional tasks evaluate performance, usability, and cognitive workload.
Gianmarco Cirelli, Enrica Stefanelli, Roberto Billardello, Christian Tamantini, Silvia Leonelli, Loredana Zollo, Luigi Pietro Cordella, Francesca Cordella   +7 more
wiley   +1 more source

Reconfiguration of Distribution Power Systems Using Heuristic Optimization Algorithms

Turkish Journal of Electrical Power and Energy Systems
Reconfiguration of the power distribution system allows for minimal real power losses and compliance with the required bus voltage limits of the power system.
Diana Akmayeva, Umut Emre Uzun, Nihat Pamuk   +2 more
doaj   +1 more source

Adaptive Autonomy in Microrobot Motion Control via Deep Reinforcement Learning and Path Planning Synergy

Advanced Intelligent Systems, EarlyView.
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi, Bairong Zhu, Haoyu Liu, Tingting Yu   +3 more
wiley   +1 more source

Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs

Advanced Intelligent Systems, EarlyView.
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza, Bruno José Olivieri de Souza, Markus Endler   +2 more
wiley   +1 more source

Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models

Angewandte Chemie, EarlyView.
AI‐empowered catalysis research via integrated database platform, universal machine learning interatomic potentials (MLIPs), and large language models (LLMs). ABSTRACT The integration of artificial intelligence (AI) into catalysis is fundamentally reshaping the research paradigm of catalyst discovery.
Di Zhang, Yuanzheng Chen, Chuanyu Liu, Yan Liu, Hongliang Xin, Jiayu Peng, Pengfei Ou, Hao Li   +7 more
wiley   +2 more sources

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source