Abstract: Energy optimization is a critical challenge in wireless sensor networks (WSNs) due to its direct impact on the network lifetime. This paper proposes the use of the K-means algorithm combined ...
Abstract: The finite resources of automated guided vehicles (AGVs) and machines in a flexible manufacturing system necessitate the integrated scheduling of production and transportation tasks to ...
Abstract: This article studies a linear quadratic mean field (LQ-MF) control model involves a global uncertainty drift and controlled diffusion. Unlike the model with additive noise, the diffusion ...
Abstract: Heuristic dispatching rules (HDRs) are widely used for solving the dynamic fuzzy job shop scheduling problem (DFJSSP). However, their performance is highly sensitive to specific scenarios ...
Abstract: In this study, a novel optimal tracker is developed for the linear quadratic tracking (LQT) problem using an output–feedback adaptive dynamic programming (ADP) framework. By leveraging the ...
Abstract: Time-series data are often affected by various forms of corruption, such as missing values, noise, and outliers, which pose significant challenges for tasks, such as forecasting and anomaly ...
Regression Task — Predicts a numerical difficulty score representing the complexity of the problem. The project is inspired by competitive programming platforms such as Codeforces and CodeChef, where ...
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