In this paper, we commence by presenting a novel notion termed Generalized Pythagorean Fuzzy Soft Expert Set(GPFSES). This innovative concept integrates pythagorean fuzzy sets with soft expert sets. Additionally, we e...
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In order to obtain a control scheme for the liquid level of unmanned platform closed drainage with good performance indicators, this paper proposes a PID control method based on the optimization of Improved Particle S...
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This research analyzes the performance loss caused by the service gateway of enterprise mobile portal to the H5 micro-apps it carries. Based on whether sensitive data is included, H5 micro applications are divided int...
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People's demand for mechatronics technology control model is increasing gradually. It is necessary to improve the control model of mechatronics technology by studying, and hybrid particle swarm optimization is an ...
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Supercapacitors are gaining significance owing to their remarkable ability to develop advanced energy storage devices for future use. In this paper, we present a new approach used to optimize the energy density of sup...
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The proceedings contain 69 papers. The topics discussed include: a study analysis of VoIP Traffic between RIP and OSPF using OPNET;FOPID corrector tuning with optimization algorithms applied on high order systems;a no...
ISBN:
(纸本)9798350326390
The proceedings contain 69 papers. The topics discussed include: a study analysis of VoIP Traffic between RIP and OSPF using OPNET;FOPID corrector tuning with optimization algorithms applied on high order systems;a novel CMOS high frequency divider;fuzzy fractional pi controller for uncertain fractional system;design of compact dual-band smartwatch antenna for biomedical applications;design of robust PID controllers based on the scenario approach;gastrointestinal endoscopic image classification using transfer learning;optimization techniques for indoor localization: a multi-objective approach to sampling time and error rate trade-off;refinement of the side information of distributed video coding with deep learning;and design of a low-cost IoT-based wearable system for cardiovascular disease detection and monitoring in Rwanda.
Electricity has evolved into a fundamental necessity for our daily lives, revolutionizing our standard of living with the convenience of devices like rice cookers, grinders, refrigerators, and air conditioners. This g...
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Edge systems are undergoing a groundbreaking computing evolution to support artificial intelligence, deep learning, and complex computational algorithms. Using cloud servers to perform deep learning model inference po...
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ISBN:
(纸本)9798350350494;9798350350500
Edge systems are undergoing a groundbreaking computing evolution to support artificial intelligence, deep learning, and complex computational algorithms. Using cloud servers to perform deep learning model inference poses challenges such as response delays, increased communication costs, and data privacy concerns. Therefore, significant efforts have been made to push the processing of deep learning models to edge systems, which has led to the creation of edge intelligence as the intersection of learning and edge computing. Learning models, especially deep convolutional neural networks, have made significant achievements in machine vision, which provide high accuracy and predictability by spending computing power and memory. If these models are optimized and deployed on edge systems, there will be a revolution in the applications of edge systems in real time. In this paper, by using optimization techniques such as quantization, weight pruning, and weight clustering, the possibility of deploying a typical convolutional neural network model on edge systems that have limited computing resources and memory is investigated. The results show that by using a collaborative algorithm, despite the slight decrease in the accuracy of the model, it is possible to achieve a small-sized model that can even be deployed on microcontrollers.
The Coati optimization Algorithm (COA) is a promising metaheuristic inspired by coati hunting behaviors, demonstrating strong performance in complex optimization tasks. However, COA encounters challenges with converge...
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This paper examines a special class of nonlinear programming problems. The problem is characterized by 1) nonlinearity of the objective function and functions defining constraints of the equality type;2) large dimensi...
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