One of the biggest developments in intelligent machines has been the development of evolving fuzzification. They are flexible system designs created using evolving methods. Fluid simulation now has excellent capabilit...
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This study introduces a novel quasi-distributed sensing system that utilizes identical weak polarization maintaining-fiber Bragg gratings (PM-FBGs) and resonance frequency mapping (RFM) for simultaneous strain and tem...
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Air pollution presents significant health and ecological dangers, especially in densely populated urban regions. This study looks at the current models that are used to guess the Air Quality Index (AQI). It does this ...
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The utilization of emerging technologies in the field of education has evolved into a valuable resource for fostering pedagogical advancements. Hence, the primary aim of this article is to assess and compare various t...
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An adaptive lion swarm optimization(ALSO) algorithm was proposed for the small-scale capacitated vehicle routing problem(CVRP). The algorithm introduces a nonlinear factor to achieve adaptive scaling adjustment of the...
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This paper gives a unique technique for automated cancer detection the use of AI-based totally prediction algorithms. Cancer often gives as a complicated and heterogeneous set of traits, making prognosis hard. In this...
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Air compressor is an important source of energy consumption in industrial production, and improving the energy efficiency is an effective strategy for promoting energy conservation and reducing emissions. The energy c...
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It is challenging to have an appropriate and simple motion control method with magnetically actuated intestinal robot. In this paper, we propose a control concept that the control system based on fuzzy control algorit...
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The human pose estimation task requires the use of visual cues and anatomical relationships between joints to locate key points. Due to the structural dependencies between human joints, it is difficult to model the de...
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The paper demonstrates the differences between two reinforcement learning methods – the Actor-Critic (AC) and the Soft Actor-Critic (SAC) applied for the benchmark pendulum and double pendulum control problems. The a...
The paper demonstrates the differences between two reinforcement learning methods – the Actor-Critic (AC) and the Soft Actor-Critic (SAC) applied for the benchmark pendulum and double pendulum control problems. The advantages and disadvantages of both methods as well as proposed modifications of the algorithms are discussed. The neural network has been developed using the Python and Tensorflow 2 libraries, and PyBullet Envs was used for environment simulations the case study.
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