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检索条件"主题词=Optimization Algorithm"

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An optimization algorithm for hurtless location of epilepsy foci

An optimization algorithm for hurtless location of epilepsy ...

引用

23rd Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

作者： Li, CY Ouyang, GH Jiang, GT Tongji Univ Coll Life Sci & Med Engn Shanghai 200092 Peoples R China

ISBN: (纸本)0780372115

The hurtless location epilepsy foci always adopts the method, which solve EEG or EMG inverse problem with the model of equal current dipole. And the optimization algorithm has much effect on the validity of computing result. This paper proposes a kind of genetic algorithms (GAs) aiming at defects of previous optimization algorithms. At the same time, we have located foci of several epileptics by collecting multi -channel EEG. The result shows that GAs has certain practical in hurtless location of epilepsy foci.

关键词： genetic algorithms optimization algorithm epilepsy foci hurtless location

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An Improved Animal Migration optimization algorithm Based on Interactive Learning Behavior for High Dimensional optimization Problem

An Improved Animal Migration Optimization Algorithm Based on...

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International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS)

作者： Lai, Zhaolin Feng, Xiang Yu, Huiqun East China Univ Sci & Technol Dept Comp Sci & Engn Shanghai Peoples R China

ISBN: (纸本)9781728104669

Animal migration optimization(AMO) algorithm inspired by the behavior of animal migration is proposed recently. AMO shows good performance on the benchmark functions whose dimensionality is no more than 30. However, the performance of AMO is degraded rapidly when the dimensionality is larger than 30. In order to overcome this shortcoming, an improved animal migration algorithm (IAMO) based on interactive learning behavior is proposed in this paper. First, we introduce an interactive learning behavior that individuals will learn from each other by exchanging information. During the search process, the search step is dynamically adjusted. In this case, the intelligence of IAMO is higher than AMO. Second, a refined search method is used to search around the current solutions, and this method can enhance the search ability of the algorithm. Third, a birth-and-death mechanism is designed to avoid local optimum. The effectiveness of IAMO is verified on 100 dimensional benchmark functions, and the empirical results show that the performance of IAMO is promising.

关键词： optimization algorithm migration interactive learning birth-and-death mechanism high dimension

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Study and Application of optimization algorithm about Sinusoidal Steady-State Circuit 34

Study and Application of Optimization Algorithm about Sinuso...

引用

34th Chinese Control Conference (CCC)

作者： Lin, Hou Xiang Qi, Li Cong, Chen Hong, Sun Shenyang Jianzhu Univ Sch Mech Engn Shenyang Liaoning Sheng Peoples R China SKLOIS Inst Informat Engn CAS Beijing 100093 Peoples R China Chinese Acad Sci Grad Univ Beijing 100090 Peoples R China

ISBN: (纸本)9789881563897

Based on Kirchhoff Law about arbitrary sinusoidal steady-state circuit network, optimization principle of dynamic design variables is adopted. Making real parts and imaginary parts of sub-circuit current and node potential as design variables, and equilibrium relation between node potential and sub-circuit current as frame-objective function, dynamic design variables optimization algorithm analysis of arbitrary complicated sinusoidal steady-state circuit network is proposed. Universal program computing sub-circuit current and node potential is completed. Practical examples are computed. Effectiveness and feasibility is verified. A new clue is set up for computing complicated alternating-current circuit network rapidly and precisely.

关键词： sinusoidal steady-state circuit network dynamic design variables frame-objective function optimization algorithm program design

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A Gravitational Artificial Bee Colony optimization algorithm and Application 8

A Gravitational Artificial Bee Colony Optimization Algorithm...

引用

8th International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)

作者： Zhang, Lingling Noncommissioned Officer Acad CAPF Hangzhou Peoples R China

ISBN: (纸本)9781538682463

In this paper, a novel Gravitational Artificial Bee Colony (GABC) optimization algorithm was proposed and utilized to the non-supervised pattern recognition problems. In this approach, the gravitational search strategy was introduced into the artificial bee colony algorithm, and a gravitational bee colony was established. The gravitational bee could search the global optimal result under the influence of both gravitational force and colony cooperation, which makes the optimization process more effectively and efficiently. Based on GABC algorithm, an intelligent kernel clustering model was established, in which the clustering center and kernel parameters were combined to be the optimal variable, while the clustering index was used as the objective function. GABC was utilized to find the optimal result of the clustering model. The standard testing functions were used to test the proposed algorithm, and GABC showed high accuracy and convergence speed. Then the testing data and fault samples were utilized to test the performance of GABC based clustering model, and its superiority on effectiveness and efficiency was demonstrated.

关键词： optimization algorithm fault diagnosis intelligent kernel clustering gravitational artificial bee colony algorithm

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Enhance the Efficiency of Sheet Beam TWT with Advanced optimization algorithm 21

Enhance the Efficiency of Sheet Beam TWT with Advanced Optim...

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21st IEEE International Conference on Vacuum Electronics (IVEC)

作者： Liu, Zeng Wang, Jianxun Wan, Yixin Liu, Qiang Luo, Yong Univ Elect Sci & Technol China Sch Elect Sci & Engn Chengdu Peoples R China

ISBN: (纸本)9781538682883

The sheet beam traveling-wave tube (SBTWT) with staggered double vane (SDV) structure has attracted much attention as a board band and powerful terahertz and millimeter-wave source. In this paper, the velocity taper for SDV structure is optimized with a recently proposed swarm-intelligence (SI) based optimization algorithm named dragonfly algorithm (DA) in order to enhance the beam-wave interaction efficiency in sheet beam TWT. The optimization result of this algorithm is compared with other commonly used algorithms. The taper optimized with DA is verified with CST particle in cell (PIC) simulations. The efficiency of the optimized structure has been greatly increased in both optimization and PIC simulations.

关键词： sheet beam optimization algorithm traveling-wave tube efficiency

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Digital audio codec based on the improved optimization algorithm of adaptive wavelets and dynamic bits allocation scheme

Digital audio codec based on the improved optimization algor...

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3rd International Conference on Signal Processing (ICSP 96)

作者： Xiong, XB Zhao, EY Department of Telecommunications Engineering Beijing University슠of Posts and슠Telecommunications

ISBN: (纸本)7505338900

This paper presents the idea of optimization algorithm of adaptive wavelets that can improve the coding algorithm to decrease the computation complexity to ten percent of that presented in the paper[5]. The full optimization of adaptive wavelets is replaced by the new method, in which the optimization is divided into two cascaded steps. And the entropy-coding-based quantization of side information is adopted so that tile bit rate is significantly reduced because it accounts for a plenty of percent of bit costs. The bit rate can decrease about 15 percent of that presented ill paper [8] by taking the method. It also coordinates with psycho-acoustics model and dynamic bits allocation scheme to make the coding noise inaudible under the condition of the least bits cost.

关键词： digital communication codecs audio coding entropy codes quantisation (signal) adaptive signal processing wavelet transforms optimisation computational complexity digital audio codec optimization algorithm adaptive wavelets dynamic bit allocation coding algorithm computational complexity reduction entropy coding based quantization side information bit rate reduction psychoacoustics model coding noise bit costs

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UUV Path Planning Based on Improved Dung Beetle optimization algorithm 9

UUV Path Planning Based on Improved Dung Beetle Optimization...

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9th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)

作者： Wu, Jinping Zhou, Yunjie Wang, Yongjie PLA Navy Submarine Acad Qingdao Peoples R China

ISBN: (纸本)9798350352573

The path planning of Unmanned Underwater Vehicle (UUV) is a crucial aspect of their operation in underwater environments, Meta-heuristic algorithms are extensively utilized for addressing UUV path planning problems. To address the limitations of the traditional dung beetle optimization algorithm (DBO), including inadequate convergence speed and precision in two-dimensional UUV path planning, and its propensity for local optima, an improved dung beetle optimization algorithm (IDBO) is introduced which employing a suite of refinement strategies. Furthermore, the solution capability of the IDBO is validated through the CEC2017 test suite and two-dimensional raster maps that replicate actual underwater environments. The simulation results demonstrate the robust problem-solving capacity of the IDBO, applicable to both benchmark functions and real-world scenarios, affirming the efficacy of the enhancement strategies in practical applications.

关键词： UUV path planning optimization algorithm DBO IDBO

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Gradient-based optimization algorithm for Hybrid Loss Function in Low-dose CT Denoising 44

Gradient-based Optimization Algorithm for Hybrid Loss Functi...

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44th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Mazandaranil, Farzan Niknejad Marcos, Luella Babyn, Paul Alirezaiel, Javad Ryerson Univ Dept Elect Comp & Biomed Engn Toronto ON M5B 2K3 Canada Univ Saskatoon Hlth Reg Royal Univ Hosp Dept Med Imaging Saskatoon SK S7N 0W8 Canada

ISBN: (数字)9781728127828

ISBN: (纸本)9781728127828

Deep learning techniques have emerged in denoising low-dose computed tomography (CT) images to avoid the potential health risks of high ionizing radiation dose on patients. Although these post-processing methods display high quality denoised images, the denoising performance still has the potential to improve. The primary purpose of this work was to determine and analyze the most effective and efficient hybrid loss function in deep learning (DL)-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. Hence, this work examined the various combinations of the most common objective functions in CT denoising networks, namely L1 loss, per-pixel loss, perceptual loss, and structural dissimilarity loss. Further, a hyperparameter learning algorithm was also introduced to find the best scalable factors of the loss functions in each hybrid loss function combination. For simplicity, RED-CNN was used in this study to easily demonstrate the performance of the losses during the denoising process. Based on this experiment, the balance between these loss function via the gradient-based optimization algorithm could help in the generalizability prediction of designing future CT denoising networks.

关键词： Medical imaging CT image denoising Deep learning RED-CNN Signal Processing Loss functions optimization algorithm

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An entropy-based model to support QoS multicast routing optimization algorithm for mobile ad hoc networks

An entropy-based model to support QoS multicast routing opti...

引用

International Conference on Wireless Communications, Networking and Mobile Computing

作者： Sun, BL Li, LY Chen, H Wuhan Univ Technol Sch Comp Sci & Technol Wuhan 430063 Peoples R China

ISBN: (纸本)078039335X

A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links. There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic nature of the network topology and restricted resources, quality of service (QoS) and multicast routing in MANET is a challenging task. In this paper, we present an entropy-based model to support QoS multicast routing optimization algorithm in mobile ad hoc networks (EQMOA). The basic motivations of the proposed modeling approach stem from the commonality observed in the location uncertainty in mobile ad hoc wireless networks and the concept of entropy. The simulation results demonstrate that the proposed approach and parameters provide an accurate and efficient method of estimating and evaluating the route stability in dynamic mobile networks.

关键词： ad hoc network entropy multicast routing optimization algorithm

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An immunity-based optimization algorithm for tuning neuro-fuzzy controller

An immunity-based optimization algorithm for tuning neuro-fu...

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International Conference on Machine Learning and Cybernetics

作者： Zuo, XQ Li, SY Ban, XJ Harbin Inst Technol Dept Control Sci & Engn Harbin 50001 Peoples R China

ISBN: (纸本)0780378652

Immune evolutionary algorithm is proposed based on the evolutionary principle in the immune system. In the algorithm, two new parameters of expansion radius and mutation radius are defined to construct a small neighborhood and a large neighborhood. Then expansion and mutation operations are designed to perform local and global search respectively by using the two neighborhoods, thus, two-level neighborhood search mechanism is realized. The results of multi-modal function optimization show that the algorithm has nice global and local searching performances. The algorithm is employed to design a neuro-fuzzy controller for real-time control of an inverted pendulum. In order to avoid the combinatorial explosion of fuzzy rules due to multivariable inputs, state variable synthesis scheme is suggested to reduce the number of fuzzy rules. Experimental results show that the designed controller can control actual inverted pendulum successfully.

关键词： artificial immune system evolutionary algorithm genetic algorithm optimization algorithm neuro-fuzzy controller

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