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Dimension shifting based intelligent algorithm framework to solve conditional nonlinear optimal perturbation

COMPUTERS & GEOSCIENCES 2023年第1期176卷

作者： Yuan, Shijin Liu, Yaxuan Zhang, Huazhen Mu, Bin Tongji Univ Sch Software Engn Shanghai 201804 Peoples R China

Conditional Nonlinear Optimal Perturbation (CNOP) method is an effective way to study the predictability of oceanic and climatic events. A framework combining the Feature Extraction method and intelligent algorithm (FEIA) is frequently used to solve CNOP because it is gradient-free and scalable at high-dimensional scales. However, the fixed latent subspace of FEIA framework makes it challenging to achieve both the quality of so-lutions and the solving efficiency. To overcome this bottleneck, this paper proposes Dimension Shifting based intelligent algorithm (DSIA) framework to solve CNOP in the large-scale model. DSIA framework adopts the dimension shifting strategy, which dynamically shifts search particles in different low-dimensional spaces. To verify the feasibility of DISA framework, we take a Regional Ocean Modeling System (ROMS) model of double-gyre variation as an experimental case. In experiments, we figure out that the selection of feature extraction method and the shifting dimension set are two influential factors for the performance of DSIA framework. Be-sides, in comparative experiments, DSIA framework yields better objective function values and more valid CNOP than FEIA framework. Moreover, convergence experiments demonstrate DSIA framework can solve CNOP with an appropriate number of function evaluations and has better convergence performance. In conclusion, exper-imental results prove that DSIA improves both quality of CNOP and solving efficiency.

关键词： Dimension shifting intelligent algorithm Large-scale optimization Dimension reduction CNOP Regional ocean modeling system

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Simulation and Optimization System of Automated E-Commerce Logistics Warehouse Allocation Network Based on intelligent algorithm

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Procedia Computer Science 2024年 243卷 100-107页

作者： Hefeng Zou School of Information and Business Management Chengdu Neusoft University Cheng Du Si Chuan China

The prosperity of e-commerce has made our lives more convenient, but the logistics behind it has been silently paying. The e-commerce industry is expanding at an unprecedented rate, and with it comes explosive growth in logistics demand, especially in the warehouse distribution link. In order to meet this demand, the warehouse distribution system needs to be improved both in terms of technology and efficiency. This rapid development also brings a series of problems. First of all is the problem of logistics congestion. Due to the surge in orders, especially during peak shopping periods, logistics centers are often under great pressure. This not only affects the speed of delivery, but can also lead to damage or loss of goods. The purpose of this paper is to find an effective method to optimize the logistics warehouse allocation system of e-commerce, and to provide an efficient and reliable logistics optimization scheme for e-commerce enterprises. In this paper, data analysis and simulation methods are used to analyze. The experimental results show that PSO has the largest improvement in the order clerk operation efficiency (13%) and the smallest improvement in the order status (1%).

关键词： E-commerce logistics intelligent algorithm warehouse allocation network simulation optimization system architecture

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Research on Data Cluster Analysis based on intelligent algorithm and Big Data Analysis

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Procedia Computer Science 2024年 247卷 664-671页

作者： Bingqing Weng Department of Tourism and Foreign Languages Ma'anshan Teacher's College Ma'anshan China

With the development of the times, computers have been continuously developed, and data analysis based on intelligent algorithms has been gradually applied. Big data analysis has become an indispensable part of various enterprises and institutions, which can help enterprises better analyze the market, optimize the overall resource allocation and decision-making efficiency, and promote the sustainable development of the overall enterprises and institutions. The purpose of this experiment is to use intelligent algorithm and big data analysis technology to cluster hotel data, so as to find the patterns and associations hidden in the data and provide decision support for the hotel industry.

关键词： intelligent algorithm big data analysis hotel data clustering cluster analysis hotel management

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Design and Implementation of intelligent algorithm Optimization Network Access Control Strategy in SDN Architecture

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Procedia Computer Science 2024年 247卷 121-128页

作者： Jianbo Luo Chengdu Neusoft University Dujiangyan Sichuan China

With the rapid progress of network technology, intelligence and virtualization have become the trend. People pay more and more attention to artificial intelligence, and the user behavior information analysis and reasoning function based on IPC and machine learning algorithm is widely used in computer applications. Traditional SDN algorithms may encounter performance bottlenecks when dealing with large-scale networks, resulting in the inability to continue to expand the network scale. This limits applications in complex network environments such as large enterprises or cloud data centers. Based on SDN architecture, this paper proposes a new intelligent optimized web crawler system, which covers user access control strategy. The research focuses on improving the IP address mapping capability, and verifies the characteristics of different node-level permissions with examples. The experimental results show that the resource utilization of the traditional algorithm is 75%, 80%, 70%, 85% and 78%, while the resource utilization of the SDN routing algorithm is above 79%, which is less than 10% higher than the traditional one. It can be seen that the intelligent algorithm shows a higher utilization of the five resources

关键词： SDN Architecture intelligent algorithm Network Access Control Strategy

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SIAP: an intelligent algorithm for multiple prescription pattern recognition based on weighted similarity distances

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BMC MEDICAL INFORMATICS AND DECISION MAKING 2023年第1期23卷 79-79页

作者： Wang, Yifei Xu, Julia Zhang, Jie Xu, Hong Sun, Yuzhong Miao, Yuan Wen, Tiancai China Acad Chinese Med Sci Wangjing Hosp Beijing 100102 Peoples R China Univ Melbourne Melbourne Vic 3010 Australia Chinese Acad Sci Inst Informat Engn Beijing 100085 Peoples R China Victoria Univ Coll Engn & Sci Melbourne Vic 3000 Australia Chinese Acad Sci Inst Comp Technol Beijing 100080 Peoples R China China Acad Chinese Med Sci Data Ctr Tradit Chinese Med Beijing 100700 Peoples R China

BackgroundClinical practices have demonstrated that disease treatment can be very complex. Patients with chronic diseases often suffer from more than one disease. Complex diseases are often treated with a variety of drugs, including both primary and auxiliary treatments. This complexity and multidimensionality increase the difficulty of extracting knowledge from clinical *** this study, we proposed a subgroup identification algorithm for complex prescriptions (SIAP). We applied the SIAP algorithm to identify the importance level of each drug in complex prescriptions. The algorithm quickly classified and determined valid prescription combinations for patients. The algorithm was validated through classification matching of classical prescriptions in traditional Chinese medicine. We collected 376 formulas and their compositions from a formulary to construct a database of standard prescriptions. We also collected 1438 herbal prescriptions from clinical data for automated prescription identification. The prescriptions were divided into training and test sets. Finally, the parameters of the two sub-algorithms of SIAP and SIAP-All, as well as those of the combination algorithm SIAP + All, were optimized on the training set. A comparison analysis was performed against the baseline intersection set rate (ISR) algorithm. The algorithm for this study was implemented with Python *** SIAP-All and SIAP + All algorithms outperformed the benchmark ISR algorithm in terms of accuracy, recall, and F1 value. The F1 values were 0.7568 for SIAP-All and 0.7799 for SIAP + All, showing improvements of 8.73% and 11.04% over the existing ISR algorithm, *** developed an algorithm, SIAP, to automatically match sub-prescriptions of complex drugs with corresponding standard or classic prescriptions. The matching algorithm weights the drugs in the prescription according to their importance level. The results of this study can help to classify and analyse

关键词： Prescriptions Drug combinations Electronic health records Traditional Chinese medicine Identification model intelligent algorithm

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Ladder network parameters identification of an isolated winding by combining the intelligent optimisation algorithm and GNIA

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第2期13卷 296-304页

作者： Ren, Fuqiang Xiao, Yao Zhan, Cao Liu, Yong Yang, Fan Ji, Shengchang Zhu, Lingyu Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Xian 710049 Shaanxi Peoples R China Zhongyuan Univ Technol Sch Elect Informat Zhengzhou 450007 Henan Peoples R China China Elect Power Res Inst High Voltage Res Inst Beijing 100192 Peoples R China

The ladder network parameter identification for transformer winding is crucial for the interpretation of the frequency response function data. The traditional identification method, mainly based on intelligent optimisation algorithm, is generally very time-consuming due to a large amount of computation. This study proposes to combine the intelligent algorithm and Gauss-Newton iteration algorithm (GNIA) to improve the optimisation efficiency notably with a sharply dropped calculation workload. These two methods are well-complementary since the intelligent algorithm holds excellent global search ability while the search of the GNIA is directional and quantitative. This study solves three key problems for the combined algorithms. The first problem is the calculation of the least-square correction solution to the network parameters in the iteration algorithm. The treatment of the ill-conditioned Jacobian matrix in the iteration algorithm is the second challenge. Another issue is the determination of the network parameter with zero sensitivity. The identification results on an isolated winding show that the combined algorithms can obtain a more precise solution with far less amount of computation.

关键词： least squares approximations Jacobian matrices Newton method transformer windings optimisation genetic algorithms frequency response search problems parameter estimation iterative methods combined algorithms ladder network parameters identification intelligent optimisation algorithm GNIA ladder network parameter identification transformer winding frequency response function data traditional identification method intelligent algorithm Gauss-Newton iteration algorithm optimisation efficiency sharply dropped calculation workload excellent global search ability identification results isolated winding show

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Point and interval forecasting system for crude oil price based on complete ensemble extreme-point symmetric mode decomposition with adaptive noise and intelligent optimization algorithm

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APPLIED ENERGY 2022年 328卷

作者： Wang, Xuerui Li, Xiangyu Li, Shaoting Beijing Jiaotong Univ Sch Math & Stat Beijing Peoples R China Dongbei Univ Finance & Econ Sch Stat Dalian Peoples R China

Stable and accurate prediction of crude oil prices is critical to national security, economic development, and even international relations, against the background of the COVID-19 and Russia-Ukraine war. Therefore, a memory-based hybrid forecasting system is established for point prediction and interval prediction of crude oil prices in this research, which more thoroughly separates the noise in the raw data and achieves superior prediction performance. There are five main steps in the proposed model: decomposing the raw data into intrinsic mode functions (IMFs) through our new data preprocessing technique complete ensemble extreme -point symmetric mode decomposition with adaptive noise (CEESMDAN), ensemble of IMFs based on memory features, prediction of reconstructed components, error correction via grey wolf optimizer (GWO) for final point prediction, obtaining interval prediction by multi-objective grey wolf optimizer (MOGWO). The empirical results prove that the proposed model has excellent accuracy, robustness, and generalization in both point prediction and interval prediction, compared with various baseline models.

关键词： Crude oil price Interval prediction CEESMDAN intelligent algorithm

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The Research of an Improved intelligent algorithm to Process Network Blocking and Its Simulation

The Research of an Improved Intelligent Algorithm to Process...

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Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

作者： Wenchuan Yang Peng Wang Chunyang Gao Yanyang Fan Huahua Luan Beijing Univ. of Post & Telecom.Beijing 100876 P.R.China

ISBN: (纸本)9781424404759

This paper mainly focuses on the construction algorithm for ad hoc virtual backbone. The virtual backbone is approximated by minimum connected dominating set in unit-disk graphs. The approximation algorithms to compute network blocking are called CDS algorithms. There are various distributed CDS algorithms. We propose improved measures based on a cost-aware algorithm. The improved algorithm optimizes the generated CDS and is simulated in VxWorks. Also we calculate the blocking probabilities for the network model and the routing scheme is the least loaded routing. After this, we also consider the blocking probabilities in the circuit-switching networks.

关键词： intelligent algorithm Network Blocking CDS.

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Malicious Node Identification Method Based on intelligent algorithm for Edge Computing

Malicious Node Identification Method Based on Intelligent Al...

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2019 International Conference on Energy, Power, Environment and Computer Application(ICEPECA 2019)

作者： Jie CHEN Ai-dong XU Hong WEN Wen-jie LIU Yi-xin JIANG Peng LI Yu-shan LI National Key Lab of Commun University of Elec.Sci.and Tech.of China EPRI China Southern Power Grid Co.Ltd.

The edge computing performs data processing at the proximity of data collecting nodes, which makes the edge computing devices also face a series of malicious attacking, such as clone node attack, Sybil node attack and so on. However, such malicious attacks are hard to identify by the traditional security measures because the illegal nodes capture the keys of the legal nodes. In order to solve the above problems, a channel information approached malicious node recognition method based on intelligent algorithm for the edge computing is proposed. The novel algorithm is feasible and the recognition accuracy meets the requirements.

关键词： intelligent algorithm Clone Node Edge Computing Sybil Node

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Optimization of Helicopter Rotor Airfoil Wind Tunnel Test Model Based on intelligent algorithm

Optimization of Helicopter Rotor Airfoil Wind Tunnel Test Mo...

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作者： Peng Kong Xiaoqiang Peng Weiguo Zhang Zhenzeng Lian Laboratory of Science and Technology on Integrated Logistics Support National University of Defense Technology China Aerodynamics Research and Development Center

The helicopter rotor wing wind tunnel test model is the basic equipment for helicopter wind tunnel test research. On the premise of meeting the requirements of corresponding strength, stiffness, natural frequency and stability, the model mass needs to be light enough to meet the requirements of heave vibration test. To this end, this paper proposes the structure of aluminum alloy skeleton + carbon fiber reinforced composite skin, and in order to obtain good performance, the following steps are used to optimize the parameters of the test model structure: 1. Establish an RBF neural network approximation model;2. Use multiple island genetic algorithm(MIGA) and the sequential quadratic programming algorithm(SQP)are combined to optimize the thickness of the skeleton and composite materials. The optimization results show that the quality of the model is reduced by 34.05% under the condition that the corresponding requirements of strength, stiffness, natural frequency and stability are met.

关键词： Carbon fiber reinforced composite Finite element analysis intelligent algorithm Multi-objective optimization,Wind tunnel test

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