This work presents a novel semi-supervised dictionary learning framework that updates the dictionary by online learning and is efficient in utilizing the training data. The method employs a two-stage process to train ...
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The progress in technology has provided opportunities for innovative solutions to intricate challenges. One possible method is employing reinforcement learning to model flying trajectories in intricate environments. G...
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ISBN:
(纸本)9798331530938
The progress in technology has provided opportunities for innovative solutions to intricate challenges. One possible method is employing reinforcement learning to model flying trajectories in intricate environments. Game development is a discipline that involves intricate reasoning and dynamic interplay between the user and the game environment. By employing several gaming engines, developers are now able to replicate real-life situations through the implementation of diverse machine learning methods. Aircraft simulation in game creation using reinforcement learning involves creating a visual depiction of real-life settings where aircraft may navigate complex environments without direct input from a human user. Currently, reinforcement learning is not widely applied in game development, particularly in simulation-based path finding techniques. This algorithm approaches possess the efficacy and capacity to generate sophisticated neural networks capable of directing an agent to do certain tasks. The aim of this project is to create aircraft simulations for game development by utilizing reinforcement-learning techniques, so that it can provide a foundational idea of the usage of this algorithm in path-detection based decision-making techniques. The goal is to demonstrate the effectiveness of reinforcement learning in a real-world scenario, where the aircraft independently assesses and selects its flying trajectory. The system will undergo testing in three distinct phases, involving the utilization of Blender3D, Unity 3D, and Anaconda prompts. The results will then be compared using TensorFlow. Several training sessions will be conducted in various environments using the Anaconda environment to optimize the outcomes. In the latter stages of development, a dynamic user interface will be implemented to enhance the user's experience. The method is anticipated to produce 152% improved AI-trained data, which can be utilized for constructing extensive simulation and game-proj
This research allows the secure surveillance approach for the Internet of Things (IoT) methodology to be developed by integrating wireless signalling and image encryption strategy. Since the Cloud Service Telco (CST) ...
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The Internet of Things (IoT) facilitates the delivery of intelligent services by sensing, gathering, processing, and exchanging data from millions of linked smart devices. The Internet of Things (IoT), which is based ...
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The main challenges of designing an antenna for modern wireless communication are size reduction and mutual coupling. An ultra-wideband (UWB) multiple input multiple outputs (MIMO) antennae with four elements is sugge...
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作者：
Majid, M.A.Effat University
College of Engineering Electrical and Computer Engineering Department Saudi Arabia
engineering the inhomogeneity, density, composition, and aspect ratio of self-assembled quantum dots (SAQDs) is essential for various applications, from broadband technologies to telecommunications. This paper investi...
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In this research, A novel approach for optimizing load shedding during power system stress conditions is introduced by combining gravitational search and particle swarm optimization (GSA-PSO) with Deep Learning. This ...
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The letter presents an algorithm, called Self-Morphing Adaptive Replanning Tree (SMART), that facilitates fast replanning in dynamic environments. SMART performs risk-based tree-pruning if the current path is obstruct...
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Machining centers (MCs) are crucial high-technology machine tools that are widely used in the manufacturing industry. Since their high investment necessities, the selection of the appropriate MC for a company is an im...
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In this paper, we study the application of using reduced order models (ROMs) for permittivity inversion to address the high nonlinearity and cycle-skipping effects in inverse scattering problems (ISPs). In this approa...
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