Mathematics, Volume 13, Issue 4

This paper is devoted to the solution of the optimal control problem. The obtained control should be optimal in terms of quality criteria and, at the same time, feasible when implemented in the control object. To solve the optimal control problem in...

T cells play a crucial role in the immune system by identifying and eliminating tumor cells. Malignant cancer cells can hijack mitochondria (MT) from nearby T cells, affecting their metabolism and weakening their immune functions. This phenomenon, ob...

Granule description is a fundamental problem in granular computing. However, how to describe indefinable granules is still an open, interesting, and important problem. The main objective of this paper is to give a preliminary solution to this problem...

The proliferation of renewable energy sources, flexible loads, and advanced measurement devices in new-type power systems has led to an unprecedented surge in power signal data, posing significant challenges for data management and analysis. This pap...

To tackle preference conflicts and uncertainty in large-group emergency decision-making (LGEDM), this study proposes a probabilistic linguistic LGEDM method integrating the Louvain algorithm and group pressure model. First, expert weights are determi...

With the rapid development of large model technology, data storage as well as collection is very important to improve the accuracy of model training, and Feature Selection (FS) methods can greatly eliminate redundant features in the data warehouse an...

Distributed frameworks for statistical estimation and inference have become a critical toolkit for analyzing massive data efficiently. In this paper, we present distributed estimation for high-dimensional quantile regression with ℓ0 constraint...

In this monograph, motivated by the work of Aphane, Gaba, and Xu, we explore fixed-point theory within the framework of C⋆-algebra-valued bipolar b-metric spaces, characterized by a non-solid positive cone. We define and analyze (FH−GH)-c...

We study investors’ information acquisition strategies under arbitrary and discrete sets of information precision and derive conditions for the existence of equilibria. When investors face information choice from general precision sets, despite...

Reinforcement Learning (RL) is a widely researched area in artificial intelligence that focuses on teaching agents decision-making through interactions with their environment. A key subset includes multi-armed bandit (MAB) and stochastic continuum-ar...