Výsledky vyhľadávania - gradient-based optimization algorithm based on the state transition function (STOBO)*

A fast optimization approach for seeking Nash equilibrium based on Nikaido–Isoda function, state transition algorithm and Gauss–Seidel technique Autor Zhou, Xiaojun, Wang, Zheng, Huang, Tingwen

“… Specifically, a dynamic state transition algorithm (STA) is proposed to seek global optima of subproblems at each iteration, and the sequential quadratic programming (SQP…”
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Gradient-based Optimization Algorithm for Hybrid Loss Function in Low-dose CT Denoising Autor Mazandarani, Farzan Niknejad, Marcos, Luella, Babyn, Paul, Alirezaie, Javad

“…)-based denoising network. Objective functions in deep learning algorithms are the main keys for optimizing the parameters of a network and can affect the quality of the denoised image significantly…”
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An RNA evolutionary algorithm based on gradient descent for function optimization Autor Wu, Qiuxuan, Zhao, Zikai, Chen, Mingming, Chi, Xiaoni, Zhang, Botao, Wang, Jian, Zhilenkov, Anton A, Chepinskiy, Sergey A

“… Although RNA genetic algorithms offer clear benefits in function optimization, including rapid convergence, they have low accuracy and can easily become trapped in local optima…”
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Developments in stochastic optimization algorithms with gradient approximations based on function measurements Autor Spall, J.C.

“…There has recently been much interest in recursive optimization algorithms that rely on measurements of only the objective function, not requiring measurements of the gradient…”
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Developments in stochastic optimization algorithms with gradient approximations based on function measurements Autor Spall, James C.

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Optimization of reward shaping function based on genetic algorithm applied to a cross validated deep deterministic policy gradient in a powered landing guidance problem Autor Nugroho, Larasmoyo, Andiarti, Rika, Akmeliawati, Rini, Kutay, Ali Türker, Larasati, Diva Kartika, Wijaya, Sastra Kusuma

“…One major capability of a Deep Reinforcement Learning (DRL) agent to control a specific vehicle in an environment without any prior knowledge is decision-making based on a well-designed reward shaping function…”
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Scaling-up topology optimization with target stress states via gradient-based algorithms Autor Mauersberger, Michael, Dexl, Florian, Markmiller, Johannes F.C.

“…•Gradient-based topology optimization was successfully used for target stress states.•Target stress states need an indirect formulation considering compliant mechanisms…”
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A consensus algorithm based on multi-agent system with state noise and gradient disturbance for distributed convex optimization Autor Meng, Xiwang, Liu, Qingshan

“… Taking these factors into consideration, in this paper a distributed algorithm with state noise and gradient disturbance is proposed for solving distributed optimization problem with closed convex…”
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Data-Driven Based State Transition Algorithm for Dynamic Optimization Autor Zhang, Yunxiang, Zhou, Xiaojun, Yang, Chunhua

“… In this paper, a novel dynamic optimization technique based on data-driven state transition algorithm (STA…”
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State transition probability based sensing duration optimization algorithm in cognitive radio Autor ZHANG Xiao, WANG Jin-long, WU Qi-hui

“… efficiencies.The relation-ship between sensing duration and state transition probability was analyzed when the licensed channel stays in the idle and busy states respectively,based on which,a state transition…”
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State transition probability based sensing duration optimization algorithm in cognitive radio Autor Zhang, Xiao, Wang, Jin-Long, Wu, Qi-Hui

“… The relationship between sensing duration and state transition probability was analyzed when the licensed channel stays in the idle and busy states respectively, based on which, a state transition…”
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Deep Forest Regression Based on Dynamic State Transition Optimization Algorithm Autor Xia, Heng, Tang, Jian, Qiao, Junfei

“… To achieved more accurate optimization process, the error change rate is used to fine-tuning the state factor during the iteration process, which is further improved with gradient-based refinement…”
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Multiagent based state transition algorithm for global optimization Autor Zhou, Xiaojun

“…In this paper, a novel multiagent based state transition optimization algorithm with linear convergence rate named MASTA is constructed…”
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A Multi-Agent Centralized Strategy Gradient Reinforcement Learning Algorithm Based on State Transition Autor Sheng, Lei, Chen, Honghui, Chen, Xiliang

“… strategy gradient algorithm grounded in a local state transition mechanism. In order to solve this challenge, the algorithm learns local state and local state-action representation from local observations and action values, thereby establishing…”
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State-Transition-Algorithm-Based Underwater Multiple Objects Localization With Gravitational Field and Its Gradient Tensor Autor Zhao, Tingting, Tang, Jingtian, Hu, Shuanggui, Lu, Guangyin, Zhou, Xiaojun, Zhong, Yiyuan

“… To deal with this issue, a global optimization algorithm, named as the state transition algorithm (STA…”
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Dynamic optimization based on state transition algorithm for copper removal process Autor Huang, Miao, Zhou, Xiaojun, Huang, Tingwen, Yang, Chunhua, Gui, Weihua

“… A novel dynamic optimization method based on the state transition algorithm (STA) is investigated for solving this problem, and to improve…”
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A State Transition Algorithm based Convolutional Neural Network Optimization Method to Froth Flotation Monitoring Autor Du, Yangyi, Zhou, Xiaojun

“… Therefore, a state transition algorithm (STA) based CNN optimization framework is proposed in this paper…”
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Transition state performance optimization of propfan engine based on DDPG algorithm Autor Zheng, Hua, Yang, Zhao-xing, Wang, Ya-fan, Zhao, Dong-zhu

“… This paper studies the performance optimization control of propfan engine based on deep reinforcement learning algorithm…”
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Broad reinforcement learning based adaptive state transition algorithm for global optimization Autor Du, Yangyi, Zhou, Xiaojun, Yang, Chunhua, Gui, Weihua

“…The state transition algorithm (STA) is an efficient intelligent optimization method with superior search capabilities in diverse applications, while its key operator selection strategies depend on manual design…”
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An Analysis of Optimization for Car PBS Scheduling Based on Greedy Strategy State Transition Algorithm Autor Yu, Fengxiao, Peng, Yipu, Li, Jian, Zhou, Guangqi, Chen, Li

“… This is achieved by establishing a multi-objective mixed-integer optimization scheduling model for PBS and solving the model using a state transition algorithm based on the greedy strategy…”
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