Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-06-06 Cooperative journals: 《计算机应用研究》
Abstract： Pose graph optimization (PGO) is a high dimensional non-convex optimization algorithm widely used in the field of computer vision. It is hard to solve directly and mainly relies on iterative techniques. It requires high quality of initial value which is difficult to be guaranteed in practice. This paper studied PGO problem and proposed a simple closed solution algorithm for pose graph based on eigen decomposition. This algorithm first developed the semidefinite relaxation of maximum-likelihood estimation (MLE) for PGO problems. Then it transformed MLE into eigen decomposition problem, and designed an improved model reduction method to solve the problem by using the sparsity of data, which further improves the computational speed of the algorithm. The algorithm has the advantages of scalability, low computational cost and high precision. Finally, experimental evaluation on simulated and real-world pose-graph datasets shows that the proposed algorithm can optimize the pose graph quickly without compromising accuracy.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-06-06 Cooperative journals: 《计算机应用研究》
Abstract： In the practical application of medical service system, under the short supply of doctor seats, traditional double-queue independent queuing system is inadequate for sufficient utilization of hospital resources. In this regard, we built a dynamic system to allocate reasonably the capacity of each outpatient queuing system without increasing the current hospital resources. Furthermore, we modeled the dynamic overflow outpatient queuing system to improve the traditional double-queue independent queuing system, and considered the probability of exiting system under perceptual and rational factors to analyze accurately the real condition of system. With the help of ProModel, a flexible and reliable discrete event simulation software, we analyzed and compared visually the dynamic model with traditional outpatient queuing model. The simulation results show that the average queue length, waiting time of patients and other service indices of the new overflow queuing model are superior to those of traditional queuing model.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-05-10 Cooperative journals: 《计算机应用研究》
Abstract： Absrtact: Aiming at the shortcomings of SBO(School Based on Optimization) algorithm, such as poor search performance and local optimization, this paper proposed SBO algorithm integrated with educational psychology(SBO based Educational Psychology, SBO-EP) . The teaching stage used the theory of "zone of proximal development" to carry out dynamic teaching for students in groups to improve the exploration ability of algorithms; It introduced the theory of "achievement motivation" into the self-study stage, and designed dynamic self-study methods according to the achievement motivation of each group of students to improve the development ability of algorithms; After each round of learning process, refer to the "peer effect" theory, to set up the class reorganization operation to increase the diversity of solutions. This paper used 40 CEC2021 test functions and 20 other types of test functions for numerical experiments, and compared SBO-EP algorithm with ant colony optimization algorithm, spherical vector-based particle swarm optimization, Archimedes optimization algorithm, gray wolf optimization algorithm, teaching and learning algorithm, cognitive psychology teaching-learning-based optimization and student psychology based optimization algorithm. The results show that SBO-EP algorithm has obvious advantages in convergence speed, optimization accuracy and stability. Finally, conducted a comparative experiment on the combination of the three strategies, verify the effectiveness of the improved strategy.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-05-10 Cooperative journals: 《计算机应用研究》
Abstract： In order to improve the accuracy and efficiency of the feature point matching, this paper proposed a novel feature point matching algorithm in terms of vision and inertial measurement unit (IMU) fusion. Firstly, the algorithm calculated the point diffusion function using the motion information of IMU to remove motion blur, and improved the feature point matching rate. Secondly, based on LK (Lucas-Kanade) optical flow method, this paper introduced gradient error and uses L1 parametric to simulate sparse noise. Furthermore, the feature point position by using IMU is the initial value of the algorithm, and then this paper used BB (Barzilar-Borwein) step to improve the efficiency of the algorithm. Finally, the comparison experiments show that the efficiency and accuracy of the algorithm are better than the LK optical flow method. Especially, the algorithm improves the localization accuracy and robustness of the VINS-Mono framework on the dataset EuRoC.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-05-10 Cooperative journals: 《计算机应用研究》
Abstract： Facing the current situation of load uncertainty, new energy grid integration, and “dual carbon” target in the power system, the paper established a real-time pricing model considering load uncertainty and carbon trading in the context of the smart grid with full consideration of the welfare of both supply side and user side. Based on the advantages that reinforcement learning can handle variable complexity, non-convex, and nonlinear problems, this paper used the Q-learning algorithm in reinforcement learning to solve the model iteratively. Firstly, this paper transformed the real-time interaction process between the user and the power supplier into a Markov decision process corresponding to the reinforcement learning framework. Secondly, the process represented the information interaction between the user and the power supplier as the iterative exploration of the agent in a dynamic environment. Finally, this paper found the optimal value by the Q-learning algorithm in reinforcement learning, i. e. , the maximal social welfare value. The simulation results show that the proposed real-time pricing strategy can effectively enhance social welfare and reduce total carbon emissions, which verifies the feasibility and effectiveness of the proposed model and algorithm.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-04-07 Cooperative journals: 《计算机应用研究》
Abstract： To address the problems of large operating costs and fairness between doctors and patients in the current hospital bed scheduling, this paper proposes a multi-objective stochastic programming model for single department bed allocation considering hospital operating costs and patient fairness. First, this paper proposes a weighted measure of responsiveness and access to reflect the fairness of the doctor-patient relationship based on relevant hospital-based policies, and establishes a multi-objective stochastic programming model considering the operational cost of the hospital; second, to facilitate the algorithm solution, a linearization method is introduced to process the complex model into a mixed integer linear model; finally, the improved NSGA2 algorithm solve the multi-objective problem The improved algorithm enhances the convergence and diversity of the algorithm, and the experimental results verify the validity and applicability of the model by adjusting different parameters for different numerical experiments.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2020-09-28 Cooperative journals: 《计算机应用研究》
Abstract： In order to solve the problem of large deviation between Hidden Markov Model and actual equipment health diagnosis, this paper developed an improved Degenerated Hidden Markov Model (DGHMM) with a core of the quasi power relation. First, the model adopted the degradation factors, modeling the process of recession for the equipment’s continuous decrease in performance. Compared with the conventional exponential accelerated degradation, the quasi power relation accelerated degradation can better describe the process that the performance of the equipment decreases gradually with the increase of service age. Then, the improved genetic algorithm can replace the conventional EM algorithm for parameters’ estimation, which overcomes the limitation that the EM algorithm is easy to fall into local optimization. At the same time, in terms of the limitation of life prediction problem as a result of the Hidden Markov Model must obey exponential distribution, an algorithm named greed & approximation based on approximation algorithm and Viterbi algorithm came out, and to seek maximum probability remaining observation, for the purpose of seeking maximum probability dynamically surplus state path, to predict the residual life of equipment. Finally, the proposed method is validated and evaluated with the data set of caterpillar hydraulic pumps. The results show that the method of equipment health diagnosis and life prediction based on the improved degraded hidden Markov model is more effective in describing equipment’s degeneration and the accuracy of equipment state diagnosis, and is also feasible in the prediction of residual life.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2020-09-28 Cooperative journals: 《计算机应用研究》
Abstract： There are various solution models for the emergency service facility location problem and this paper studies the P-center model. This paper proposed a backtracking algorithm with upper and lower bound, and the algorithm added a reduction algorithm by studying the mathematical properties. The algorithm can decrease the scale and the degree of complexity of the problem, so as to accelerate the execution speed. At the end of the paper, this paper illustrated an instance to elaborate this algorithm further.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2020-09-28 Cooperative journals: 《计算机应用研究》
Abstract： This paper proposed the mathematical model which based on the open location routing problem with fuzzy demands considering with the sum of location cost, routing cost, lost opportunity and additional distances. For solving the mathematical model, this paper proposed a new swarm intelligence algorithm named hybrid discrete mushroom algorithm. The artificial wind replaced by partly mapping crossover and path relinking algorithm; And the local search strategy replaced by the method of selecting different neighborhoods with a certain probability; Stochastic simulation simulated the designed routes to compute additional distances and lost opportunity resulting from serving failure. The algorithm successfully applied to the combinatorial optimization problems under the condition of retaining the original characteristics of the algorithm. Finally, verify the validity of the mode and the performance of hybrid discrete mushroom reproduction algorithm through a series of tested instances and comparisons.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2020-09-28 Cooperative journals: 《计算机应用研究》
Abstract： Considering the two-level e-commerce supply chain composed of an e-commerce platform and a third-party logistics service provider as the research object, aiming at the moral hazard problem caused by the third-party logistics service provider's complete control of its own logistics service level, this paper analyzes the strategy of using blockchain to prevent the moral hazard of the third-party logistics service provider. With the help of the logistics service level monitoring framework based on blockchain, considering the two scenarios of adopting blockchain and not adopting blockchain, the Stackelberg game model between e-commerce platform and the third party logistics service provider under decentralized decision-making is established, and the changes of supply chain profits before and after the application of blockchain and the correlation with technology cost input are studied. After that, the correctness of the conclusion is verified by numerical analysis. The results show that when the cost input of blockchain is controlled within a certain range, the application of this technology can effectively reduce the moral hazard of the third-party logistics service providers, improve the profits of the whole supply chain, promote the improvement of the profits of each node of the supply chain, and help the healthy and orderly development of the supply chain.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-04-01 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the high conflict problem of fresh cold chain logistics service quality evaluation information, the improved Evidence Reasoning (ER) method was used to process the indicator evaluation information. Firstly, considering the uncertainty of the expert's assessment of the indicators of the fresh cold chain logistics service providers, the ER method was proposed to process indicator evaluation information of each supplier. Secondly, consider the evaluation of each supplier by each expert. The information has a high degree of conflict. The cosine similar function was used to measure the degree of conflict change. The evidence weights were used to calculate the weight of the evidence and the evaluation information is corrected. Then, the evidence reasoning method was used to integrate the revised supplier evaluation information. Finally, an enterprise selected the fresh cold chain logistics service provider as an example for analysis, and compared the analysis results with the results calculated by the comparison method. The results show that the proposed method can effectively solve the high conflict problem and reduce the uncertainty caused by the conflict.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-04-01 Cooperative journals: 《计算机应用研究》
Abstract： The current trust-based recommendation algorithms did not fully exploit the trust relationship between users and it lacked reasonable trust transitivity rules, which greatly affected the reliability and accuracy of the recommendation algorithm. Aiming at the above problems, this paper combined user rating data with the user's social relationship to build a trust transitivity model, and proposes a recommendation algorithm based on trust transitivity. Firstly, the algorithm uses the score data to calculate the implicit direct trust relationship of the users in the trust transitivity model. Secondly, the indirect trust relationship of multiple trust transitivity chains is solved by solving the ordered weighted average operator. Finally, it converge the user’s trust and similarity into comprehensive similarity for predictive recommendation. The experimental results show that the proposed algorithm can effectively improve the recommendation quality of the system.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-04-01 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the problems that the traditional recommendation algorithm ignores the influence of the tight structure of social network structure on user trust transmission and the lack of social psychological explanation, a recommendation algorithm based on link prediction for directed interaction and user trust is proposed. Firstly, the similar user circle of the target user is identified by the integrated similarity between the user preference behavior and the social circle. Secondly, the directional interaction influence between the target users is obtained by combining the node gravity index and the directed influence factor. The integrated user trust value of the directional interaction influence and the user score trust finds a trustworthy similar user set in the similar circle of friends of the target user, which effectively improves the accuracy of the recommendation and finally generates the recommendation. The results show that the proposed method has a significant improvement in performance compared to the previous social network recommendation algorithm.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： In the background of smart grid, in connection of the shortage of fossil energy and the high pressure of peak-time power supply, this paper developed a method of complementary power supply of photovoltaic and fossil fuel. It constructed a real-time pricing model of user-side microgrid based on social welfare maximization. In the model, the power supplier coordinated the two types of energy sources by real-time pricing. Besides, this paper designed a real-time pricing algorithm to solve the model. The simulation results show that compared with the large power grid using fossil energy alone, the complementary power supply mode can effectively reduce the power supply of fossil energy and electricity price in peak time slots, and enhances the social welfare. The method offers a reference for the effective management of smart grid in future.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-28 Cooperative journals: 《计算机应用研究》
Abstract： To solve the vehicle routing problem with time window for the shortest length of vehicle travel and the minimum number of the using vehicles, this paper proposed a cultural wolf pack algorithm. To improve the quality of the wolf pack, this paper constructed the initial wolf pack according to the customer's nearest neighbor matrix. Considering the features of this problem and the wolf pack algorithm, this paper redefined the intelligent behaviors of artificial wolves. The mutation of leader wolf increased the searching range of the optimal solution. According to the favorable information of the current optimal solution, this paper constructed the knowledge of the belief space to guide the evolution direction of the wolf pack and improve the search efficiency. Simulation results show that the cultural wolf pack algorithm can get less number of vehicles, shorter total distance and better stability than other algorithms.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-03 Cooperative journals: 《计算机应用研究》
Abstract： The operation scheduling in the presence of uncertainty factors lead to inability to obtain accurate time of operation and ends under Emergency Rescue Situation. In order to solve the problem, this paper proposed a grey scheduling model and a hybrid grey cuckoo algorithm. The model used three parameters interval grey number and the four parameters of interval grey number to describe the uncertain time of operation and the uncertain ends. Then, it defined the possibility measure and necessity measure to estimate the probability of operation tardiness. After that, this paper established a gray mixed integer programming model with minimize average credibility of operation tardiness, and presented a solution method of the mixed grey cuckoo search algorithm. A classic example of size 6(3) � verified the proposed algorithm. The results show that the algorithm can solve the problem very well, and the performance is better than the basic cuckoo algorithm.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-03 Cooperative journals: 《计算机应用研究》
Abstract： In view of the uncertainty of demand and return for perishable products in different periods, a multi-period model of closed-loop logistics network for perishable product and the corresponding mixed integer linear programming (MILP) model were proposed, so as to achieve the decision of the minimum total system cost, the best facility location and vehicle route. In order to avoid the influence of uncertain parameters effectively, some defined constraints in the model were converted to robust corresponding expressions by using cardinality constrained robust approach. Through the case of the fruit and vegetable agricultural enterprises of Shanghai, the validity of model was verified by genetic algorithm (GA) . The result shows that compared with the single period system, the multi-period system had the advantages of dynamic performance and lower system cost, meanwhile, the feasibility and effectiveness of the robust model were verified through the analysis of the variation of uncertain budget parameters, which provides a reference for the construction of multi-period closed-loop logistics network and the reduction of system cost under uncertain environment.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-12-13 Cooperative journals: 《计算机应用研究》
Abstract： This paper studies the dynamic allocation model of hospital emergency resources in response to the imbalance between supply and demand of emergency resources in hospitals under emergencies. The emergency resource supply in the hospital is relatively scarce due to the increase in the number of patients and the evolution of the patient's injury. Based on the sequential decision theory, this paper designs the changes of patient needs into a Markov decision process and establishes a dynamic allocation model of hospital emergency resources . Then the model is solved by using the basic particle swarm optimization algorithm, which is analyzed by a rescue example of the hospital after an earthquake. The case study shows that the Markov decision-making process can dynamically meet the needs of patients in different states under the evolution of injuries, making the overall resource utilization in emergency rescues to be optimal.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-11-29 Cooperative journals: 《计算机应用研究》
Abstract： This paper adopts fuzzy theory to create the fuzzy parameter of the return by history data of similar products and uses Mean-variance model to carve and estimate return and risk. Moreover, based on adapting Cobb-Douglas production function to building the multi-criteria optimal function, the optimal sequence strategy model is built. Then, integrating the fuzzy simulation and multi-criteria 0-1 genetic algorithm can solve the model. Lastly, the numeral example shows the optimal strategy that is derived by model is superior to the strategy that only other five sequence strategies.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-10-11 Cooperative journals: 《计算机应用研究》
Abstract： This paper proposed a back distribution algorithm for output values, which was to solve the random setting problem about input weights and hidden layer thresholds on traditional extreme learning machine. On the basis of traditional extreme learning machine, the algorithm obtains the optimal output value distribution coefficient through the optimization method, and uses the least squares method to determine the network input parameters. Experiments on common data sets show that, the proposed algorithm not only achieves good learning and generalization ability compared with other improved extreme learning machine algorithms, but also can obtain a simple network structure and it is effective.
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