Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-12-13 Cooperative journals: 《计算机应用研究》
Abstract： Concern the problem that the traditional association analysis algorithms cannot efficiently and accurately mine the user's potential temporal association control habits which are implied in the user's operation records, this paper proposed a novel user temporal association control habits mining method based on FP-Growth. This method includes three stages: to generate the transaction set, the temporal frequent item set, and the final temporal association control habits via the user operation-action forest, the improved FP-Growth algorithm and a time constraint rule. Finally, the comparative experiments by using the real user control records show that this method can improve the efficiency of transaction set generation and can more accurately discover the user’s temporal association habits of smart home devices.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-08-13 Cooperative journals: 《计算机应用研究》
Abstract： This paper proposed A BP neural network short-term power load forecasting algorithm based on maximum deviation similarity criterion to solve the problem of strong randomness, low stability and poor prediction accuracy. This method first modified the maximum deviation similarity criterion algorithm, and proposed to use the load feature vector of the forecast day and the distance of the center load characteristic after clustering to determine the similar day class of the forecast day. Then, it used the similar daily class load data after clustering as the training data of BP network, and output the load of three consecutive days for 96 points. The experiment shows that the short-term power load forecasting method proposed by this paper has great improvement in precision and network training time, and has high effectiveness and practicability.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-20 Cooperative journals: 《计算机应用研究》
Abstract： The real-time safety state evaluation of urban road traffic is an important research content of intelligent transportation system (ITS) . Focusing on the problem that the evaluation results of the existing traffic safety state real-time evaluation methods are unsatisfactory, this paper proposed a safety state evaluation method of urban road traffic based on video information. Firstly, this paper analyzed the rapid detection method of traffic flow parameters based on video information. Then, it proposed the concept of velocity dispersion of urban road from the point of view of vehicle speed dispersion. Finally, it established a safety state evaluation method of urban road traffic based on road velocity dispersion. The experimental results show that the proposed method can evaluate the safety state level of urban road traffic in real time and in a reasonable way, . And the evaluation result can provide the corresponding basis for the traffic management department to develop effective urban road traffic safety improvement program.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-20 Cooperative journals: 《计算机应用研究》
Abstract： In order to reduce the impact of communication delay on the system to achieve consensus, this paper investigates the leader-following consensus of the second-order nonlinear multi-agent systems with active leader. It presents the concept of an approximate random pulse delay, and designed a new control protocol to make the system achieve the leader-following consensus. Compared with the traditional protocol, when the pulse time communication delay is small, the agents in the new protocol predict their current state of time based on the delay state and send the prediction state to each adjacent agent, which compensate for its own feedback channel delay meanwhile. Based on the Lyapunov stability theory, using the nature of a kind of generalized Halanay inequality obtains two sufficient conditions which can guarantee the reaching of leader-following consensus of systems. Finally, the simulation of the example verifies the superiority of new protocol.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-02 Cooperative journals: 《计算机应用研究》
Abstract： Public buses have unique characteristics, such as fixed moving paths and time periods, uniform vehicular device standards, low risk of privacy exposure. This paper designed a public bus network-based vehicular crowd sensing system, considering the characteristics of public buses. In the system, data center utilizes public buses of the bus network to collect urban data which is required by data users. It also studied the task assignment problem and the data trading problem in the system. This paper proposed an optimized task assignment strategy based on a greedy algorithm to minimize the system energy consumption of data collection, and proposed an optimal data trading strategy based on game theory to maximize the system utility. Finally, numerical results demonstrate the effectiveness of proposed strategies.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-02 Cooperative journals: 《计算机应用研究》
Abstract： Association rules mining is an important research topic in data mining. Big data processing puts forward higher requirements for the efficiency of association rules mining algorithm, where the most time consuming step is frequent pattern mining. For the problem that the state of art frequent pattern mining algorithm is not efficient, a frequent pattern mining algorithm based on interval interaction and transaction mapping (IITM) is proposed, which combines Apriori algorithm and FP-growth algorithm. This algorithm just needs to scan the dataset twice to generate the FP tree, and then scan the FP tree to map the ID of each transaction to the interval. It growths the frequent pattern by interval interaction and solves the problem that the Apriori algorithm needs to scan the dataset multiple times, the FP-growth algorithm needs to iterate to generate the conditional FP tree, which reduce the efficiency of the frequent pattern mining. Experiments on real dataset show that the IITM algorithm is superior to Apriori, FP-growth, and PIETM algorithms at different support.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-24 Cooperative journals: 《计算机应用研究》
Abstract： For complex event detection in the mass real-time data from multiple sources, there is a problem of low accuracy and inefficiency in the triage of original event streams. This paper proposed a method of complex event detection based on an event tree. Firstly, defining dependencies between events, then take full account of the multi-dependencies between atomic events to generate atomic event trees and form the list with the dependent event trees, increasing the number of effective detection of complex event processing engines, such that the matching efficiency of event detection is improved. Meanwhile, this method reduces the memory consumption and improves the throughput of event detection. Simulation experiments and case studies demonstrate the advantages and feasibility of this method on massive data processing.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-19 Cooperative journals: 《计算机应用研究》
Abstract： To make research results more realistic , this paper studied the consensus of multi-agent systems with uncertainties and randomly occurring nonlinearities and time delay via impulsive control with topology switching. In the traditional protocol, it is usually assumed that the communication delay between adjacent individuals is the same as the communication delay between individual and leader, but this is conservative. In the new protocol, the size of delay above can be different. Compared with traditional research methods, the approach that deals with the delay in complex network synchronization research is introduced into the research of consensus of multi-agent systems. Using a generalized Halanay inequality , two sufficient conditions which are not related to the delay are given to meet the leader-following consensus of systems with topology switching, in other words, the delay does not affect the final consensus of system when the relevant parameters satisfy the theorem’s conditions. Compared with the decision conditions with delay on other methods, the results of this study are less conservative. The numerical simulation verifies the feasibility of the new protocol.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-12 Cooperative journals: 《计算机应用研究》
Abstract： Inferring causal directions from observed variables is one of the fundamental problems in artificial intelligence (AI) field. Traditional conditional independence based methods usually learn causal directions by detecting V-structures and return Markov equivalence classes, instead of true causal structures; Most other direction learning methods can distinguish the equivalence classes, but are effective only in the bivariate (or two-dimensional) cases. This paper proposed a new approach for causal direction inference from general networks, based on a split-and-merge strategy. The method first decomposes an n-dimensional network into n induced subnetworks, each of which corresponds to a node in the network. Each induced subnetwork can be subsumed to one of the three substructures: one-degree, non-triangle and triangle-existence structures. Three effective algorithms are developed to infer causalities from the three substructures, and learning these induced subnetworks orderly to achieved the whole causal structure of the multi-dimensional network. Experiments show that the method is more general and effective than traditional methods.
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