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检索条件"任意字段=3rd Euro-NF Conference on Network Control and Optimization"

共 1643 条记录，以下是101-110 订阅

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Subspace Structured Neural network for Rapid Trajectory optimization 3

Subspace Structured Neural Network for Rapid Trajectory Opti...

引用

3rd Modeling, Estimation and control conference (MECC)

作者： Tituana, Luis Xu, Yunjun Univ Cent Florida Mech & Aerosp Engn Orlando FL 32826 USA

ISBN: (纸本)9781713872344

In this study, finite horizon constrained trajectory optimization is tackled by using Artificial Neural network with an embedded subspace manifold. The resulting network takes advantage of the reduced dimension search space guided by a bio-inspired motion rule. The input nodes of the network are interpreted as collocation points over the time domain transcribed by a pseudospectral discretization method. The activation function for each node is the inverse of the dynamical system. The weights and biases to be optimized in the network are analogous to the parameters of the motion rule. The network is optimized during training by minimizing an augmented loss function where the constraints are considered penalties. The proposed method is simulated in a collision avoidance trajectory planning problem of a mobile robot with two driving wheels and an attitude slewing maneuver problem of an asymmetric rigid body spacecraft.

关键词： Trajectory optimization Neural networks Optimal control

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Research on Training Set optimization and Fault Diagnosis Method Based on CNN Algorithm 24

Research on Training Set Optimization and Fault Diagnosis Me...

引用

3rd International conference on Computer, Artificial Intelligence and control Engineering, CAICE 2024

作者： Cai, Xinyu College of Business Jiaxing University Jiaxing314001 China

ISBN: (纸本)9798400716942

Addressing the issue of low accuracy in traditional mechanical bearing fault diagnosis models, a training set optimization and fault diagnosis method based on the CNN (Convolutional Neural network) algorithm is proposed. The process begins with segmenting the training data, from which multiple feature values in each segment are extracted to form a feature matrix. These matrices then create the feature training set. A convolutional neural network model is subsequently established for training this set. Fault feature classification is achieved using a Softmax classifier. Experimental results show that the training set optimization method can accurately extract data features and reduce the volume of data required for model training. This enhancement in training efficiency and model classification accuracy is evident, with the method maintaining high accuracy even in noisy conditions. © 2024 ACM.

关键词： Convolutional neural networks

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Power Grid optimization Planning Based on Particle Swarm Algorithm 3

Power Grid Optimization Planning Based on Particle Swarm Alg...

引用

3rd International conference on Electrical Engineering and control Science, IC2ECS 2023

作者： Liu, Guangmao Du, Xiao Guo, Xueli Yao, Nan Zheng, Gang Wang, Shuang Grid Henan Electric Power Company Nanyang Power Supply Company Nanyang City China

ISBN: (纸本)9798350382426

As a critical component of future power systems, the proactive distribution network faces new challenges in its expansion planning. Firstly, the paper introduces a three-state weather model for the probability of distribution network line failures due to disasters. Subsequently, a bi-level model for distribution network expansion planning is established, where the upper-level model optimizes the planning of new distribution network lines, and the lower-level model plans the positions and capacities of DG units. A two-layer nested particle swarm optimization algorithm is employed to optimize and solve the model. Finally, through simulation analysis of a specific case study, the effectiveness and feasibility of the proposed method are validated. The research results indicate that considering extreme weather factors in planning can significantly enhance the reliability and adaptability of proactive distribution networks, providing valuable insights for the sustainable development of future power systems. © 2023 IEEE.

关键词： DG Location and Capacity Fault Probability Particle Swarm Algorithm

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Detection and Prevention of Tomato Leaf Disease using Convolutional Neural network and Inception Net 3

Detection and Prevention of Tomato Leaf Disease using Convol...

引用

3rd IEEE International conference on Intelligent Techniques in control, optimization and Signal Processing, INCOS 2024

作者： Ajitha, E. Nivedha, V. Parvathi, B. St.Joseph's Institute of Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350361186

A state-of-the-art technique for analyzing images that is still relatively new but yields consistent results is Deep Learning(DL). Many DL techniques are used for leaf disease categorization. Regardless of the cuisine, tomatoes are a staple in every kitchen and are one of the most popular vegetables. It ranks third in terms of widespread production, behind sweet potatoes and potatoes. The number and quality of tomato crops are, however, impacted by several illnesses. An approach to crop disease diagnosis by deep learning is used. For disease categorization and detection, a Convolutional Neural network is employed. Two pooling and two Convolutional layers are employed inside the model. The suggested model beat pre-trained InceptionV3, and VGGI6, according to the experiment findings. 98% training accuracy and 88.17% testing accuracy were attained by the CNN model. © 2024 IEEE.

关键词： Convolutional neural networks

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Research on Grouping Strategy of Feeders in Distribution network Considering the Importance Degree of Tie Switches 3

Research on Grouping Strategy of Feeders in Distribution Net...

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3rd International conference on Power Systems and Electrical Technology, PSET 2024

作者： Chen, Minghui Luo, Longbo Wu, Renbo Wang, Haocheng Gao, Hongjun Liu, Junyong Guangzhou Power Supply Bureau Guangdong Power Grid Co. Ltd. Guangzhou China Sichuan University College of Electrical Engineering Chengdu China

ISBN: (纸本)9798350353204

This article proposes a quantitative method for the importance of tie switches in distribution networks. Firstly, a combination of stack and depth priority is used to search for the load supply path in the distribution network. Based on this, combined with the theory of load chain power supply, the substitutability of tie switches and their load recovery ability are analyzed to obtain a quantitative method for the importance of tie switches. Afterwards, a complex distribution network feeder grouping strategy based on redundant switches and non critical tie switches was proposed, which is conducive to the simplification analysis of complex distribution networks. Finally, through numerical analysis, the quantitative results of the importance of tie switches and the grouping situation of complex distribution networks were demonstrated. © 2024 IEEE.

关键词： Power distribution networks

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Diagnosing the Early Stages of Alzheimer’s Disease by Applying the Modified Ant Colony optimization Technique 3rd

Diagnosing the Early Stages of Alzheimer’s Disease by Apply...

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3rd International conference on Computing and Communication networks, ICCCN 2023

作者： Kumari, Rashmi Das, Subhranil Singh, Raghwendra Kishore School of Computer Science Engineering and Technology Bennett University Greater Noida India Dehradun India School of CS and AI SR University Warangal India

ISBN: (纸本)9789819726707

Treating Alzheimer’s Disease (AD) and preventing further degeneration are becoming increasingly important. Doctors who could view many morphological aspects for improved clinical practices would evaluate patients more extensively. Previous studies have shown the value of applying deep learning to T1-weighted MRI images to differentiate AD from Normal control. This paper proposes the classification of three binary classifications by applying 3D CNN network. A Modified Ant Colony optimization (MACO) technique is proposed for optimizing the different weights of the network. The effectiveness of the proposed model is assessed by using a sample of 259 ADNI individuals. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ant colony optimization

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3rd control conference Africa, CCA 2024 - Proceedings

3rd Control Conference Africa, CCA 2024 - Proceedings

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3rd control conference Africa, CCA 2024

The proceedings contain 33 papers. The topics discussed include: model predictive control of an underground mine cooling water operation;automatic tuning of level controllers in a flotation bank using Bayesian optimization;multi-objective feed reservoir control via optimal pump scheduling;an assessment of engagement, experience, and attitudes after participation in the girls in control workshop;community farm monitoring toolkit: design and implementation of a low-cost tool for sustainable community based agricultural projects in Africa;optimization of the Paris wastewater treatment plants and sewer network: preliminary results;model-plant mismatch detection using the plant-model ratio: the influence of multivariable systems containing both fast and slow dynamics;time based stiction compensation;modelling of consumer dynamics to improve fuel gas blending control;improvement of model predictive control on a depropaniser: an industrial case study;a comparison of two methods of adaptive nonlinear model predictive control;a generalized anti-windup approach for internal model control;a lean path for learning control in undergraduate electronics programs;and a comparison of two methods of adaptive nonlinear model predictive control.

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Optimal Scheduling of Solar PV Generators and network Assets in Distribution network 3rd

Optimal Scheduling of Solar PV Generators and Network Assets...

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3rd International conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2023

作者： Singh, Samarendra Pratap Kanwar, Neeraj Saraswat, Amit Department of Electrical Engineering Manipal University Jaipur Rajasthan Jaipur India

ISBN: (纸本)9789819784288

Load flow study (LFS) and optimal power flow (OPF) are the two important tools for power system operation and control. LFS determines the state variables of electrical network whereas OPF picks the best one among the set of load flow solutions while respecting the limits of state variables. This paper presents OPF model for optimal scheduling of solar PV generators (SPVGs), tap changer (TC) and switched capacitor banks (SCBs) in distribution network. The model considers minimization of two separate objective functions, the first one is line losses and the second is the curtailment of available solar PV power. The OPF model is implemented on the modified IEEE 33 bus distribution network, and solved using Particle Swarm optimization (PSO) using DIgSILENT PowerFactory software. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Load flow optimization

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Sizing and Performance Analysis of a Battery Energy Storage System in Bangladesh Distribution System 3

Sizing and Performance Analysis of a Battery Energy Storage ...

引用

3rd International conference on Power, control and Computing Technologies, ICPC2T 2024

作者： Alam, Md Ashraful Basu, Mayur Kabir, Kazi Meharajul Saber, Ahmed Optimization and AI ETAP CA United States Auburn University Department of ECE AL United States Prairie View AandM University Department of ECE TX United States

ISBN: (纸本)9798350349207

This paper aims to evaluate and determine the appropriate size of a battery energy storage system within Bangladesh's distribution system. The country frequently experiences load shedding due to a substantial in-crease in local loads, particularly during peak hours. A larger-scale lithium battery bank, independent of any generating sources connected to the grid, could be an excellent solution. An optimal strategy is devised to identify the most suitable lo-cation for establishing the battery bank, considering the check and balance between the required load demand and the grid's integrity and reliability. This system has a minimum cost and ensures a probability of loss of power supply (PLPS) below 5%. For the case study, a comprehensive power network in Bangladesh is simulated using the ETAP platform to analyze the system's sizing and performance compared to other models. As a result, a substantial enhancement in the power system's reliability and quality is achieved cost-effectively. © 2024 IEEE.

关键词： Lithium batteries

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Multi-fidelity deep neural network surrogate model for aerodynamic shape prediction based on multi-task learning 3

Multi-fidelity deep neural network surrogate model for aerod...

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3rd International conference on Energy and Power Engineering, control Engineering (EPECE)

作者： Wu, Pin Liu, Zhitao Zhou, Zhu Song, Chao Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China China Aerodynam Res & Dev Ctr State Key Lab Aerodynam Mianyang 621000 Sichuan Peoples R China

ISBN: (纸本)9798350366105;9798350366099

With the increasing demands of refined aerodynamic shape design for modern aircraft, it is very essential for aerodynamic shape optimization to obtain more accurate aerodynamic data. The widely used high-fidelity simulation is usually accurate but extremely time-consuming. Therefore, we propose an innovative multi-fidelity model based on multi-task learning for aerodynamic shape prediction. This model consists of Bezier-Auxiliary Classifier GAN (Bezier-ACGAN), Multi-gate Mixture-of-Experts and Multi-Fidelity (MMoE-MF). Firstly, Bezier-ACGAN is used to construct the subsonic and transonic datasets and is used as an intelligent parameterization method. Secondly, The MMOE-MF model is coupled with the parameters of Bezier-ACGAN to predict different-fidelity of aerodynamic data. The results show that the predicted results of the optimal airfoils agree with the results of high-fidelity simulation well. This method is a promising approach that can convert from low-fidelity data to high-fidelity data in a few seconds.

关键词： Bezier-Auxiliary Classifier GAN Multi-gate Mixtureof-Experts multi-task learning multi-fidelity surrogate model

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