Aimed at the problems of low solution precision and easy to be trapped into local optima by single objective evolutionary algorithm, a self-adaptive multi-objective optimization algorithm based on nondominated sorting...
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Aimed at the problems of low solution precision and easy to be trapped into local optima by single objective evolutionary algorithm, a self-adaptive multi-objective optimization algorithm based on nondominated sorting genetic algorithm II(NSGA2) and Label Propagation Algorithm(LPA) is proposed. The algorithm takes Kernel K-means(KKM) and Ratio Cut(RC) as the objective functions. Two new crossover operator and the improved mutation operator is used to achieve the evolution of the population. We conducted simulation experiments in the computer-generated networks and the real-world networks environment. The results show that compared with other community detection algorithms, our algorithm has the advantages of high resolution and strong search ability, and it can effectively identify the community structure in complex networks.
Human action recognition technology has been applied to intelligent security surveillance, content-based image and video retrieval and natural user interface. How to make use of the new type of data, 3D skeleton joint...
Human action recognition technology has been applied to intelligent security surveillance, content-based image and video retrieval and natural user interface. How to make use of the new type of data, 3D skeleton joint position extracted by 3D depth camera, has been a highly active research topic. A posture representation model is proposed, which is invariant to limb length, length ratio between body parts and body orientation. This model contains polar angle and azimuthal angle of each limb in the spherical coordinate system which is established by the features of body joints. Hidden Markov Model（HMM） is exploited for recognition. Skeleton sequences of different body orientation are collected as experimental data. Experimental results demonstrate the effectiveness of our approach.
作者：
Peng YaoXi-Zhao WangBig Data Institute
College of Computer Science and Software Engineering Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen Guangdong China
In cost sensitive classification problems we often suppose to have a known cost matrix in which each element represents the cost of mistakenly classifying an object from one class into another. Weighted least square, ...
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ISBN:
(纸本)9781538652152
In cost sensitive classification problems we often suppose to have a known cost matrix in which each element represents the cost of mistakenly classifying an object from one class into another. Weighted least square, which does not equally consider individual classes and therefore assigns a different weight to each class of samples, is a typical approach to dealing with cost sensitive classification problems. Theoretically and experimentally it is confirmed that reasonable class weights will greatly improve classification ability of a learning model. Unfortunately we only know that these weights depend generally on cost matrix but very few methods can be used to specifically determine these weights according to cost matrix. This paper proposes a weighted least square (WLS) model of random weight network and then successfully uses the model in cost sensitive classification. A genetic algorithm to determine weights of different sample classes based on a cost matrix is given. Model analysis and experimental simulations are conducted. Considering the total misclassification cost as the evaluation index, a comparative study shows that our WLS model is far superior to the existing cost sensitive ELM and cost sensitive naive Bayes models.
For the problems of extracting question trunks and focus extraction completely by conventional dependency syntax parsing, this paper presents a method of question trunks and focus extraction oriented to question depen...
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For the problems of extracting question trunks and focus extraction completely by conventional dependency syntax parsing, this paper presents a method of question trunks and focus extraction oriented to question dependency syntax conversion with the characteristics of the questions. The method defines a number of combining rules of question dependency relations. According to the rules, we do merger, conversion and removal to parts component of question syntax, and extract the question trunks and focus based on question dependency syntactic structure. The experimental results show that the proposed method of question trunks and focus extraction based on dependency syntax conversion achieved good results.
r the problem that many different classification of questions and answers and users changing from one interest to another,we propose a personalized user model based on multi-kernel support for vector data domain descr...
r the problem that many different classification of questions and answers and users changing from one interest to another,we propose a personalized user model based on multi-kernel support for vector data domain description (MSVDD).
With the continuous development of artificial intelligence technology, deep learning technology is used to process a large number of real-time traffic scene information helping the management of public transportation,...
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With the continuous development of artificial intelligence technology, deep learning technology is used to process a large number of real-time traffic scene information helping the management of public transportation, and traffic flow statistics can reflect the real-time traffic conditions. The paper uses the EfficientDet target detection algorithm to detect and analyze the traffic video frame information and carry out statistics of vehicle and pedestrian flow at traffic *** system can calculate the vehicle speed and perceive the degree of traffic congestion in real-time. It's convenient for the traffic department to increase the utilization rate of the road.
In this paper, we obtain asymptotic formulas for k-crank of k-colored partitions. Let Mk(a, c;n) denote the number of k-colored partitions of n with a k-crank congruent to a mod c. For the cases k = 2, 3, 4, Fu and Ta...
With the rapid increase in the volume of dialogue data from daily life, there is a growing demand for dialogue summarization. Unfortunately, training a large summarization model is generally infeasible due to the inad...
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Video try-on is a challenging task and has not been well tackled in previous works. The main obstacle lies in preserving the details of the clothing and modeling the coherent motions simultaneously. Faced with those d...
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Considering that travel routing costs change with time against the background of reverse logistics, this paper presents the time dependent vehicle routing problem of simultaneous delivery and pick-up (TD-VRPSDP), and ...
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ISBN:
(纸本)9781424445424
Considering that travel routing costs change with time against the background of reverse logistics, this paper presents the time dependent vehicle routing problem of simultaneous delivery and pick-up (TD-VRPSDP), and establishes the mixed integer programming model of TD-VRPSDP. The pheromone updating strategy based on rank-based ant colony system and max-min ant system algorithm are used for solving TD-VRPSDP. Time heuristic in ant colony system (ACS) is designed for the constraint of dynamic routing characteristics and time windows in TD-VRPSDP. Eight group test instances are generated in the numerical simulation experiments. The results show that the ACS designed in this paper can solve TD-VRPSDP well.
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