关键词：
Sociology;Statistics;Path planning;Heuristic algorithms;Optimization;Monitoring;Mobile robots;Path planning;improved firefly algorithm;self-adaptive population size
摘要：
In the simulation experiment of path planning of mobile robot based on firefly algorithm, it is found that the matching relationship between the number of fireflies and obstacles in the iterative process has significant conflict impacts on exploration ability and computational complexity of the algorithm. In order to solve the above problem, an optimal method of path planning based on firefly algorithm with self-adaptive population size is proposed. Firstly, the evaluation of degree of collision is established at the cost of avoiding collision. Based on the degree of collision of the population, two nonlinear functions are proposed to determine the population size. Then, individuals are added or deleted for the firefly population. Individuals are added randomly. The feasible solution and the infeasible solution are distinguished in firefly population, and delete the fireflies in the infeasible solution first when performing the eliminating operation. Finally, on the basis of the existing methods for dealing with infeasible paths, a coefficient that is adaptively adjusted according to the population size is introduced to control the degree to which the infeasible path approaches the feasible area. Compared with fixed population size firefly algorithm, the proposed algorithm has better performance in terms of solution stability, convergence speed and running time.
期刊：
International Journal of Internet Protocol Technology,2019年12(4):181-189 ISSN：1743-8209
通讯作者：
Hou, ZX
作者机构：
[Huawei Wu] Hubei Univ Arts & Sci, Hubei Key Lab Power Syst Design & Test Elect Vehi, Xiangyang 441053, Peoples R China.;[Huawei Wu] Hubei Univ Arts & Sci, Sch Automot & Traff Engn, Xiangyang 441053, Peoples R China.;[Yicheng Li] Jiangsu Univ, Automot Engn Res Inst, Zhenjiang 212013, Jiangsu, Peoples R China.;[Yong Kuang] Dongfeng Xiangyangtouring Car Co Ltd, Jinfeng Rd,Dongfeng Motor Ave, Xiangyang City, Peoples R China.;[Zhixiang Hou] Changsha Univ Sci & Technol, Coll Automobile & Mech Engn, Changsha 410076, Hunan, Peoples R China.
通讯机构：
[Hou, ZX ] ;College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha, China
关键词：
Communication channels (information theory);Switching;Channel;Intelligent switching;Mobile communications;Non-uniform distribution;Scatterer;Mobile telecommunication systems
摘要：
In the presence of non-uniformly distributed scatterer medium, mobile communication is prone to multipath effect, so in order to improve the communication stability by reducing multipath interference through intelligent switching of mobile communication channels, an intelligent switching algorithm for mobile communication under non-uniform distribution of scatterers based on time compression and spatial focusing is proposed. Simulation results show that the proposed method can provide good intelligence in the switching of mobile communication channels under non-uniform distribution of scatterers and it improves channel equalisation, provides output communication signals with good spatial focusing capability and reduces transmission delay and inter-symbol interference.
期刊：
International Journal of Information and Communication Technology,2019年14(2):251-261 ISSN：1466-6642
通讯作者：
Hou, Zhixiang(736688480@qq.com)
作者机构：
[Hou, Zhixiang; Gao, Jiakun] College of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Hunan;410114, China;[Hou, Zhixiang; Gao, Jiakun] 410114, China
通讯机构：
College of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Hunan, China
关键词：
Congestion control (communication);Data transfer;Energy utilization;Vehicle to vehicle communications;Vehicle transmissions;Vehicular ad hoc networks;Beacon;Channel;Congestion control mechanism;Congestion prediction;Data transmission models;Network congestions;VANET;Vehicle communications;Traffic congestion
摘要：
In view of the low pointing accuracy problem of the hanging wire weight control method adopted in current mechanical arm control, for the control of the mechanical arm, a mechanical intelligent arm position control method based on continuous trajectory point control is proposed to improve the control accuracy of mechanical intelligent arm. The kinematic behavior planning model of the mechanical arm in six degree of freedom motion space is constructed. The end-effect inverse kinematics decomposition method is used to obtain the vector set of mechanical arm joint rotation. The parametric self-tuning regulation is used to control parameters optimization. Continuous trajectory point control method is adopted to improve the accuracy of mechanical intelligent arm position change and achieve high-precision arm control. Simulation results show that six degree of freedom mechanical intelligent arm accuracy control has higher precision, minimized convergence error and higher robustness with this control method.
摘要：
As China's urbanization process continues to advance and deepen, the spatial structure within each city is changing constantly. Analyzing the hidden relationship between human and land behind the massive urban data is a hot topic. In this paper, we apply the idea of network embedding to urban geography. The high-dimensional urban human activity data is embedded into the low-dimensional space (feature space) using the node2vec method. Compared to the traditional method of directly using high dimensional data analysis, node2vec can better detect the spatial relationship and structure of the network which are important for us to understand the urban functional areas more clearly. Based on Shanghai taxi data and subway travel data, we focused on the distribution and characteristics of functional areas in Shanghai. Then we verified the feasibility and superiority of node2vec.
期刊：
Journal of Applied Science and Engineering,2018年21(1):45-50 ISSN：2708-9967
通讯作者：
Sun, Yan(736688480@qq.com)
作者机构：
[Sun, Yan] Xi'an Fanyi University, Xi'an, Shaanxi, 710105, China;[Hou, Zhixiang] College of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, 410114, China
通讯机构：
Xi'an Fanyi University, Xi'an, Shaanxi, China
期刊：
Journal of Applied Science and Engineering,2018年21(1):25-32 ISSN：2708-9967
通讯作者：
Hou, Zhixiang(736688480@qq.com)
作者机构：
[Zhang, Yuchi] Hunan Industry Polytechnic, Changsha, Hunan, 410082, China;[Hou, Zhixiang] College of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, 410114, China
通讯机构：
College of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, China
关键词：
Back-propagation model;dam foundation;grouting pressure control;robust propotional–integral–derivative control
摘要：
<jats:p>For the security of grouting process of dam foundation, grouting pressure control is one of the most important problems. In order to avoid dangerous grouting pressure fluctuation and improve the control precision, a feedback propotional–integral–derivative control method was presented for the whole grouting system. Because the grouting pressure is affected by many factors such as grouting flow, grouts density, and geological conditions, the parameters of propotional–integral–derivative must be tuned. In this article, the adaptive tuning method is presented. The back-propagation artificial neural networks model was proposed to simulate the grouting control process, and sensitivity analysis algorithm based on orthogonal test method was adopted for the selection of input variables. To obtain the optimal propotional–integral–derivative parameters, an iteration algorithm was used in each sampling interval time and the discrete Lyapunov function of the tracking error. The simulation results showed that self-learning propotional–integral–derivative tuning was robust and effective for the realization of the automatic control device in the grouting process.</jats:p>
摘要：
Nanoparticles are extensively used in various fields because of its surface and quantum size effects. Therefore, the measurement of nanoparticle size is of great significance to the development of nanotechnology. In order to accurately measure nanoparticles, dynamic light scattering particle technology can be used. However, it needs to solve the integral equation during measurement. In order to solve this problem, regularization inversion algorithm is proposed and designed a particle measurement system in this paper. The experimental results show that the inversion algorithm can accurately measure the particle size of nanoparticles and provide a reference for the development of dynamic light scattering particle technology.
期刊：
Journal of Applied Science and Engineering,2017年20(4):483-490 ISSN：2708-9967
通讯作者：
Hou, Zhixiang(736688480@qq.com)
作者机构：
[Hou, Zhixiang; Xie, Ping; Hou, Jiqiang] College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan, 410004, China
通讯机构：
College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan, China
摘要：
In order to ensure the safe and stable operation of electric vehicles (EV), it is necessary to accurately estimate the state of charge (SOC) of power lithium battery for electric vehicle. Because of the nonlinear relationship between SOC and its influencing factors, RBF neural network has obvious advantages in solving nonlinear problems, so in this paper, an SOC estimation method of power battery based on RBF neural network is proposed. In order to improve the accuracy of SOC estimation, we use particle swarm optimization (PSO) to optimize the RBF neural network model and identify the value of RBF network center vector and the weights through global optimal searching ability of PSO algorithm. The results simulation show that the SOC model based on PSO-RBF neural network has good estimation accuracy.
摘要：
In the practical application of thermoelectric Generation Technology for vehicle exhausts waste heat, the output power and conversion efficiency of thermoelectric module cannot reach the maximum value at the same time. In order to solve the problem of matching output power and conversion efficiency of thermoelectric Generation Technology for vehicle exhausts waste heat, this paper makes a theoretical analysis of the output power and conversion efficiency of thermoelectric module, expounds the factors that affect the output power and conversion efficiency of thermoelectric module, establishes the matching relationship between the output power and conversion efficiency, it builds theoretic foundation for thermoelectric generator design.
摘要：
Air fuel ratio is a key index affecting the emission of gasoline engine. In order to accurately control the air fuel ratio and overcome the existed transmission delay of air fuel ratio signal, a multi-step predictive control method of air fuel ratio based on neural network was provided in the paper. The simulation was accomplished using experiment data of HL495 gasoline engine, and the results show the air fuel ratio error is less than 3% in the faster throttle movement and it is less than 1.5% in the slower throttle movement.
期刊：
Mathematical Structures in Computer Science,2014年24(5):e240501 ISSN：0960-1295
通讯作者：
Hou, Zhixiang
作者机构：
[Hou, Zhixiang] College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha, China Email: icicta2012@gmail.com
通讯机构：
[ZHIXIANG HOU] C;College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha, China Email: icicta2012@gmail.com
关键词：
Bridges;Software design;Category theory;Intelligent computation;Mathematical structure;Theoretical computer science;Computation theory
摘要：
Mathematical Structures in Computer Science bridges the gap between theoretical computer science and software design. By publishing original perspectives from all areas of computing, the journal stresses applications from logic, algebra, geometry, category theory and other areas of logic and mathematics. Through issues such as this special issue, the journal also plans to play an occasional, but important role in the fields of intelligent computation and automation.
摘要：
Method of transit priority signal control of isolated intersection is researched in the paper for an intersection at east door south road and spring breeze road in Shenzheng. In which, the delay of each passenger is used as new index to evaluate the control effect. The results show that the method of transit priority signal control of isolated intersection is better than the before, which could reduce the delay and give expression to the ideal "people first".
会议名称：
3rd International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2011)
会议时间：
JAN 06-07, 2011
会议地点：
Shanghai, PEOPLES R CHINA
会议主办单位：
(1) College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan 410076, China
关键词：
Gasoline Engine;Multi-Sensor Data Fusion;Neural Network;Air Inflow Velocity;Modeling
摘要：
A neural network-based multi-sensor data fusion prediction model of air inflow velocity under working condition is proposed and a neural network topology of air inflow velocity prediction under transitional working condition is set in this paper to mitigate the air-fuel ratio control inaccuracy resulting from air flow sensor lag. Simulation is conducted on the basis of HQ495 engine experimental data, which shows that neural network-based multi-sensor data fusion prediction model of air inflow velocity, with better accuracy, excels engine average value model.
摘要：
Although road traffic accidents have contingency characteristics, but also can use the method of forecasting theory to forecast. In this paper, we adopt the gray GM (1,1) model and cubic exponent smooth model to optimum combination,Established traffic accident prediction model based on IOWGA(induction ordered geometric weighted average)and tested this combination forecasting model. Test results show that the combination forecasting model is effective, reliable, high prediction accuracy, can used to real forecast.
