This paper explores the application of the Ant Colony Optimization (ACO) algorithm in optimizing analog circuits, specifically focusing on the two-stage operational amplifier (op-amp) with Miller compensation. The des...
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ISBN:
(数字)9798350353983
ISBN:
(纸本)9798350353990
This paper explores the application of the Ant Colony Optimization (ACO) algorithm in optimizing analog circuits, specifically focusing on the two-stage operational amplifier (op-amp) with Miller compensation. The design process adheres to initial technical constraints and employs the Figure of Merit (FoM) as the objective function to assess circuit quality. The ACO algorithm mimics the foraging behavior of ants, utilizing pheromone distribution and probabilistic improvement to guide the search towards the optimal solution (i.e., the highest FoM). Simulation data from Cadence Virtuoso with the 65nm process is used to construct a Python-based implementation of the ACO algorithm to determine the optimal circuit parameters that satisfy the initial design constraints.
This document presents the results of a master-slave methodology developed to address the issue of reducing energy losses in electrical distribution systems by locating and sizing photovoltaic generators and distribut...
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ISBN:
(数字)9798331516901
ISBN:
(纸本)9798331516918
This document presents the results of a master-slave methodology developed to address the issue of reducing energy losses in electrical distribution systems by locating and sizing photovoltaic generators and distribution static compensators. The master phase utilizes several optimization techniques, including the vortex search algorithm, the particle swarm optimization, the Chu & Beasley genetic algorithm, and the generalized normal distribution optimizer, to determine the optimal location and size of each component. In contrast, the slave stage uses the three-phase version of the successive approximations method to evaluate the objective function. To validate the efficacy of this approach, it was tested on both a 25-node and a 37-node system. The study demonstrates a novel approach that minimizes energy losses by integrating two elements into the distribution power system simultaneously. The findings indicate that vortex search outperforms the other three optimization methods in reducing energy losses, reducing losses by 56.3301 % for the 25-node system and 44.1870 % for the 37-node system. Using its programming environment, all the numerical validations were carried out in the MATLAB software version 2024a.
For enhanced performance and efficient operation of a fuel cell (FC) power system, it is indispensable to estimate its intrinsic parameters precisely. Then only, a proper design of the FC system can be accomplished. H...
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ISBN:
(数字)9798350354379
ISBN:
(纸本)9798350354386
For enhanced performance and efficient operation of a fuel cell (FC) power system, it is indispensable to estimate its intrinsic parameters precisely. Then only, a proper design of the FC system can be accomplished. Here, the parameter estimation problem is articulated in the form of an unique objective function to be minimized. The total of squared deviation (TSD) between the experimental and estimated FC stack voltages is considered to be the objective function. Here, a modified grey wolf optimization algorithm (MDGWOA) is implemented to optimally estimate the parameters of different proton exchange membrane fuel cell (PEMFC) stacks. In the past, many evolutionary approaches were proposed for FC parameter estimation. MDGWOA showcases improved accuracy as compared to other approaches in terms of lesser TSD which is evident from the comparative results.
China is the leader of the global electric vehicle (EV) industry, while Tesla and BYD are the market leaders of the Chinese EV industry. The competition between Tesla and BYD EVs is an important driver of innovation a...
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In optimal transport, quadratic regularization is a sparse alternative to entropic regularization: the solution measure tends to have small support. Computational experience suggests that the support decreases monoton...
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This paper develops a novel characterization for random utility models (RUM), which turns out to be a dual representation of the characterization by Kitamura and Stoye (2018, ECMA). For a given family of budgets and i...
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By sorting out the operational mechanism of hard and soft weapons, this paper analyzes the mutual influence of hard and soft weapons and equipment on operational effectiveness and the emergence of collaborative applic...
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ISBN:
(数字)9798350370805
ISBN:
(纸本)9798350370812
By sorting out the operational mechanism of hard and soft weapons, this paper analyzes the mutual influence of hard and soft weapons and equipment on operational effectiveness and the emergence of collaborative application. Take the problem of equipment application in the mission of against the low orbit giant constellation as an example, this paper distinguishes the operational intensity and puts forward the collaborative application strategy of hard and soft weapons. Taking maximization of equipment operation efficiency and minimization of resource consumption as the objective function, a coordinated application model of soft and hard killing weapons characterized by unified combat effectiveness is constructed, which lays a foundation for forming the optimization plan of equipment application.
Gradient descent algorithms are widely considered the primary choice for optimizing deep learning models. However, they often require adjusting various hyperparameters, like the learning rate, among others. These hype...
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ISBN:
(数字)9798350372816
ISBN:
(纸本)9798350372823
Gradient descent algorithms are widely considered the primary choice for optimizing deep learning models. However, they often require adjusting various hyperparameters, like the learning rate, among others. These hyperparameters significantly impact both the speed of convergence and the accuracy of the solution. Thus, this study introduces an analytical framework that uses mathematical models to assess the mean error of each objective function concerning gradient descent algorithms. Additionally, this framework aims to identify the most effective hyperparameter values by minimizing the mean error. By analyzing optimization models, generalized principles have been established for setting hyperparameter values. Empirical results demonstrate that our proposed method achieves superior convergence efficiency and reduced errors compared to existing approaches.
In this paper, a control method based on Nash equilibrium is proposed for the formation control of a group of quadrotor aircraft. Firstly, the dynamics and kinematics models of the quadrotor aircraft are established. ...
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ISBN:
(数字)9798350368604
ISBN:
(纸本)9798350368611
In this paper, a control method based on Nash equilibrium is proposed for the formation control of a group of quadrotor aircraft. Firstly, the dynamics and kinematics models of the quadrotor aircraft are established. Then, according to the kinematics and dynamics model of the quadrotor aircraft, the decision variable of the quadrotor aircraft is selected and the objective function of the quadrotor aircraft is designed. By analyzing the objective function of quadrotor aircraft, the Nash equilibrium solution of multi-quadrotor aircraft system is obtained. Finally, the feasibility and superiority of the proposed control method are verified by simulation experiment and comparative test.
In recent years, the energy field has prioritized low-carbon and clean development. Animal husbandry offers significant potential for emission reduction, and optimizing the integrated energy system of farms is a key s...
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ISBN:
(数字)9798350353563
ISBN:
(纸本)9798350353570
In recent years, the energy field has prioritized low-carbon and clean development. Animal husbandry offers significant potential for emission reduction, and optimizing the integrated energy system of farms is a key solution to reducing carbon emissions in this sector. This paper presents the framework for the integrated energy system of large-scale dairy farms. It models the distributed energy and energy storage equipment in the system, formulates the objective function and constraint conditions for optimal system operation, and analyzes the optimal operation of two different scale dairy farms. Optimizing the integrated energy system of large-scale dairy farms can promote energy conservation and emission reduction, improve energy utilization efficiency, and provide technical support for the realization of low-carbon and clean development of animal husbandry.
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