Abstract: In order to solve the problems of excessive carbon emissions and environmental pollution caused by the current carbon trading policy, this paper breaks the traditional annual carbon trading ...
Abstract: Lithium-ion batteries (LIBs) are being intensively studied and universally used as power sources for electric vehicle applications. Despite the staggering growth in sales of LIBs worldwide, ...
Abstract: Pedestrian behavior modeling and simulation play a critical role in traffic safety, urban planning, and transportation system optimization. In traffic environments, these models are used to ...
Abstract: The second-generation hybrid and Electric Vehicles are currently leading the paradigm shift in the automobile industry, replacing conventional diesel and gasoline-powered vehicles. The ...
Abstract: The increasing prevalence of chronic non-communicable diseases makes it a priority to develop tools for enhancing their management. On this matter, Artificial Intelligence algorithms have ...
Abstract: Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure proper ...
Abstract: In this paper, the concept of an all-dc wind park with series-connected turbines is investigated as an alternative to the classical ac parallel or radial wind park. This paper presents a ...
Abstract: Adaptive grasping is an important approach for robotic grippers to handle objects with irregular shapes. Compared to rigid-link-based adaptive grippers, the continuum-structure grippers ...
Abstract: This paper describes a multiobjective optimization design technique for a six-phase copper rotor induction motor mounted with a scroll compressor to achieve minimum manufacturing cost and ...
Abstract: This article presents a method for diagnosing and identifying open-phase fault and current sensor fault in dual three-phase permanent synchronous motor (DTP-PMSM) drives. The fault diagnosis ...
Abstract: This article studies the detection of discontinuous false data-injection (FDI) attacks on cyber–physical systems (CPSs). Considering the unknown stochastic properties of the process noise ...
Abstract: This article addresses the problem of path following for underactuated unmanned surface vessels (USVs) formation via a modified deep reinforcement learning with random braking (DRLRB). A ...