The process to determine the unknown parameters of a battery model using experimental data is known as parameter identification of lithium-ion batteries utilizing optimization techniques. This challenge is solved by u...
详细信息
The proceedings contain 344 papers. The topics discussed include: image defogging based on joint contrast enhancement and multi-scale fusion;face tracking by fusing convolutional neural networks and particle filtering...
ISBN:
(纸本)9781665472784
The proceedings contain 344 papers. The topics discussed include: image defogging based on joint contrast enhancement and multi-scale fusion;face tracking by fusing convolutional neural networks and particle filtering;construction of LC filter integrated circuit and analysis of control system function;privacy preserved federated learning for skin cancer diagnosis;research on the control under the participation of heat storage device and fast cut back control strategies in isolated grid;large-scale energy storage battery technology participates in the application of AGC frequency modulation in thermal power plants;intelligent monitoring and analysis system for boiler combustion based on big data;research on the platform of metrological inspection calibration;inverter fault diagnosis algorithm based on midpoint voltage deviation polarity and topology reconstruction;next point-of-interest recommendation for cold-start users with spatial-temporal meta-learning;the influence of axial flux leakage from motor coils on the magnetic bearing and shielding measures;a common-mode voltage suppression oriented modulation method for modular multilevel converters;chance-constrained energy management strategy for micro-grids intra-day operation;and an improved support vector machine attack detection algorithm for industry controls system.
This paper revisits the classical Linear Quadratic Gaussian (LQG) control from a modern optimization perspective. We analyze two aspects of the optimization landscape of the LQG problem: 1) connectivity of the set of ...
详细信息
This paper revisits the classical Linear Quadratic Gaussian (LQG) control from a modern optimization perspective. We analyze two aspects of the optimization landscape of the LQG problem: 1) connectivity of the set of stabilizing controllers C-n;and 2) structure of stationary points. It is known that similarity transformations do not change the input-output behavior of a dynamical controller or LQG cost. This inherent symmetry by similarity transformations makes the landscape of LQG very rich. We show that 1) the set of stabilizing controllers C-n has at most two path-connected components and they are diffeomorphic under a mapping defined by a similarity transformation;2) there might exist many strictly suboptimal stationary points of the LQG cost function over C-n and these stationary points are always non-minimal;3) all minimal stationary points are globally optimal and they are identical up to a similarity transformation. These results shed some light on the performance analysis of direct policy gradient methods for solving the LQG problem.
The proceedings contain 27 papers. The topics discussed include: dynamic generation of dilemma-based interactive narratives;a lightweight intelligent virtual cinematography system for machinima production;SquadSmart: ...
ISBN:
(纸本)9781577353256
The proceedings contain 27 papers. The topics discussed include: dynamic generation of dilemma-based interactive narratives;a lightweight intelligent virtual cinematography system for machinima production;SquadSmart: hierarchical planning and coordinated plan execution for squads of characters;automatic design of balanced board games;personality-based adaptation for teamwork in game agents;interactive storytelling: a player modelling approach;automatic rule ordering for dynamic scripting;sorts: a human-level approach to real-time strategy AI;learning a table soccer robot a new action sequence by observing and imitating;a believable agent for first-person shooter games;motivational ambient and latent behaviors in computer RPGS;level annotation and test by autonomous exploration: abbreviated version;from synthetic characters to virtual actors;and a comparative analysis of story representations for interactive narrative systems.
Breast cancer is a type of cancer in which the breast cells grow out of control. It is one of the leading cause for the high pace of death in women. Breast cancer classification is mainly done with the help of Machine...
详细信息
This paper discusses the style of information service by robot partners. In order to perform information service suitable to each person, the robot partner should extract the preference and daily behavior patterns of ...
详细信息
ISBN:
(纸本)9783642165863
This paper discusses the style of information service by robot partners. In order to perform information service suitable to each person, the robot partner should extract the preference and daily behavior patterns of the person. Therefore, we propose a learning method of the relationship between human interaction and its corresponding behavior of the robot partner. In this paper, we use a robot music player;miuro, and we focus on the music selection for providing the comfortable sound field for the person. The experimental results show that the proposed method can learn the relationship between human interaction and its corresponding behavior, and that the proposed method can provide the person with the preferable song as the comfortable sound field. Furthermore, we show the seamless sharing of information between different types of robot partners.
With the prosperity of online social networks, more and more users have multiple social accounts at the same time in heterogeneous social networks. Associating the same user identity between different social networks ...
详细信息
ISBN:
(纸本)9781450362047
With the prosperity of online social networks, more and more users have multiple social accounts at the same time in heterogeneous social networks. Associating the same user identity between different social networks is beneficial for applications such as across-network information diffusion and cross-domain recommendation. User identity association across distinct social networks is to find accounts belonging to the same user without knowing the real identity of the users. Most of the existing identity correlation methods, including supervised learning and unsupervised learning methods, only use user's entity information in social networks, such as user attribute information and content information, nevertheless the inherent structural information of the networks is not fully used, so their effectiveness is often sensitive to the high dimension and sparsity of feature spaces. In this paper, we propose a novel model, called EUIA, which employs network embedding method to learn two low-dimensional representations of nodes of the two original networks respectively. Besides, we learn a mapping function across the learned two low-dimensional spaces, supervised by observed anchor links, for further predicting. In addition, we propose an effective optimization program to improve the accuracy of the model. Through experiments on the dataset of Facebook, we prove that the proposed EUIA model performs much better in accuracy than other baseline methods in cross-network user identity association problem.
作者:
Xu, JinyouZhang, LeiRui, Chengjie
Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin China
In the context of engineering education, to improve the practical engineering skills of engineering students, the teaching ideas and implementation methods of the curriculum are designed based on Outcome-based Educati...
详细信息
To solve the problem that current mainstream license plate recognition methods have unsatisfactory results under unconstrained scenarios, a real-time license plate detection and recognition algorithm based on extended...
详细信息
ISBN:
(纸本)9798400709777
To solve the problem that current mainstream license plate recognition methods have unsatisfactory results under unconstrained scenarios, a real-time license plate detection and recognition algorithm based on extended YOLOv5 and PP-OCR v2 is proposed. First, the output of the YOLOv5's detection head is extended to predict four vertex coordinates of the candidate license plate, and the accurate license plate region can be located with these four vertices. Furthermore, the vertex coordinates can be used to correct the license plate image with the inverse perspective transformation. After that, the license plate image fed into the following recognition network can present a frontal view, which can effectively reduce recognition errors. Then, the lightweight text recognition network derived from the PP-OCR v2 with the recurrent layer removed is utilized to recognize the corrected license plate image. The experiment results on the public dataset CCPD show that, the proposed algorithm achieves 99.34% detection accuracy and 97.61% recognition accuracy, and the processing speed of license plate detection reaches 84FPS and license plate recognition detection reaches 667FPS under the mid-end GPU, and the processing speed of the whole license plate recognition system is 87FPS, which meets the practical real-time requirements.
We propose two algorithms achieving generalized arc consistency for the soft global cardinality constraint with variable-based violation and with value-based violation. They are based on graph theory and their complex...
详细信息
ISBN:
(纸本)3540343067
We propose two algorithms achieving generalized arc consistency for the soft global cardinality constraint with variable-based violation and with value-based violation. They are based on graph theory and their complexity is O(root nm) where n is the number of variables and m is the sum of the cardinalities of the domains. They improve previous algorithms that ran respectively in O(n (m + n log n)) and O((n + k)(m + n log n)) where k is the cardinality of the union of the domains.
暂无评论