Results 111 to 120 of about 14,317,493 (293)

Tariff-Sensitive Global Supply Chains: Semi-Markov Decision Approach with Reinforcement Learning

Systems
Global supply chains often face uncertainties in production lead times, fluctuating exchange rates, and varying tariff regulations, all of which can significantly impact total profit.
Duygu Yilmaz Eroglu
doaj   +1 more source

Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models

International Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel, Xavier Boulanger, Vegard Arneson   +2 more
wiley   +1 more source

Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning

SmartBot, EarlyView.
Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo, Rodrigo S. Jamisola Jr., Molaletsa Namoshe   +2 more
wiley   +1 more source

Reinforcement learning-based active thermal management for sustainable electric-vehicle battery packs

Results in Engineering
The rapid emergence of electric vehicles (EVs) emphasizes the importance of the adequate thermal control of lithium-ion battery systems to guarantee their safety, prolong their service life, and improve the energy efficiency.
Md. Mottahir Alam, Nader Al Sayed Hafez Ewess, Amjad Ali Pasha, Kamal M. Othman, Abdulfattah Noorwali, Esam Y.O. Zafar, Abdul Zubar Hameed, Haroonhaider Sidhwa   +7 more
doaj   +1 more source

The semi-Markov beta-Stacy process: a Bayesian non-parametric prior for semi-Markov processes

, 2020
The literature on Bayesian methods for the analysis of discrete-time semi-Markov processes is sparse. In this paper, we introduce the semi-Markov beta-Stacy process, a stochastic process useful for the Bayesian non-parametric analysis of semi-Markov ...
Peluso S.
core   +1 more source

Artificial intelligence empowers targeted protein degradation: Core technological innovations, multi‐scenario applications, and translational prospects

Smart Molecules, EarlyView.
AI is transforming TPD by improving the design, prediction, and optimization of degraders such as PROTACs, molecular glues, and LYTACs. This review summarizes key AI‐driven advances, highlights applications across drug discovery stages, and discusses remaining challenges and future directions for accelerating the development of therapies against ...
Shuanglin Qin, Rui Peng, Guangshuai Zhang, Si Yan, Jin Xiao, Zishu Liu, Ziyu Tan, Qingqing Xie, Shangjie Li, Wei Luo, Xiaohe Xiao   +10 more
wiley   +1 more source

DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection

IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley   +1 more source

Semi-Markov decision process as a safety and reliability model of a sea transport operations [PDF]

, 2010
A problem of optimization of a sea transport operation in safety and reliability aspect is discussed in the paper. To describe and solve this problem, a semi-Markov decision processes theory is applied.
Grabski, F.
core  

Estimating crippling loss from hunting with multistate models: a case study on northern bobwhites

Wildlife Biology, EarlyView.
Hunting as a recreational pursuit provides an important ecosystem service worldwide. Harvest management plays a vital role in regulating wildlife take to ensure long‐term population sustainability and meet value‐based objectives (e.g. hunter satisfaction). However, managers rarely have complete control or observability of harvest mortality.
Amanda S. Cramer, Justin A. Rectenwald, William B. Lewis, Michael A. Hazelbaker, Alexander L. Jackson, Holly K. Lott, Geoff Beane, D. Clay Sisson, Melanie R. Kunkel, Nicole M. Nemeth, James A. Martin   +10 more
wiley   +1 more source

Electric Bus Charging Schedules Relying on Real Data-Driven Targets Based on Hierarchical Deep Reinforcement Learning

IEEE Access
The charging scheduling problem of Electric Buses (EBs) is investigated based on Deep Reinforcement Learning (DRL). A Markov Decision Process (MDP) is conceived, where the time horizon includes multiple charging and operating periods in a day, while each
Jiaju Qi, Lei Lei, Thorsteinn Jonsson, Lajos Hanzo   +3 more
doaj   +1 more source