Application of Fuzzy Automata Decision-Making System in Target Control

In order to perform better in target control, this paper proposed a decision-making system method based on fuzzy automata. The decision-making system first preprocessed the signal and then performed a two-level decision on the target to achieve optimal control. The system consisted of four parts: signal preprocessing, contrast decision-making, comprehensive judgment of decision-making and decision-making result. These decision algorithms in target control were given. A concrete application of this decision-making system in target control was described. Being compared with other existing methods, this paper used both global features and local features of target, and used the decision-making system of fuzzy automata for the target control. Simulation results showed that the control effect based on the decision-making system was better than that of the other existing methods. Not only it was faster, but also its correct control rate was higher to be 95.18% for the target control. This research on the control system not only developed the FA theory, but also strengthened its application scope in the field of control engineering.

HEURISTIC PARTICLE SWARM OPTIMIZATION ALGORITHM FOR AIR COMBAT DECISION-MAKING ON CMTA

Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm optimization （HPSO） algorithm is proposed to solve the decision-making （DM） problem. HA facilitates to search the local optimum in the neighborhood of a solution, while the PSO algorithm tends to explore the search space for possible solutions. Combining the advantages of HA and PSO, HPSO algorithms can find out the global optimum quickly and efficiently. It obtains the DM solution by seeking for the optimal assignment of missiles of friendly fighter aircrafts （FAs） to hostile FAs. Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA based algorithms in searching for the best solution to the DM problem.

Forecasting and Decision-Making of Systematic Theories for Engineering Geology in Environmental Geoscience

The paper discusses the problems of engineering geology in environmental geoscience from several aspects. For natural sciences and social sciences, it deduces essential theory from logistic cycle model, logic mapping and Verhulst model. It had been discovered that these aspects are equal. However, these were the studies of normal effects. We must establish mathematical model to check from contrary course for gray forecasting and decision-making and answer several questions satisfactorily.

China＇s nuclear power under the global 1.5℃ target： Preliminary feasibility study and prospects

This study explores the measures to achieve the global 1.5 ℃ temperature rise target （1.5 ℃ target） by analyzing the feasibility and obstacles of nuclear power in China. The 1.5 ℃target imposes stricter requirements on China＇s nuclear power. Considering the available nuclear power plant sites, nuclear power layout, equipment manufacture ＆ supply, nuclear power plant construction capacity, supportive operation ＆ management talents, investment, cost effectiveness, and public acceptance, the achievement of the development objectives of nuclear power in China considering the 1.5 ℃ Target is difficult. However, it is possible if favorable decisions and policies are made.

Non-iterative image feature matching algorithm based on reference point correspondences

Based on the coded and non-coded targets, the targets are extracted from the images according to their size, shape and intensity etc., and thus an improved method to identify the unique identity（D） of every coded target is put forward and the non-coded and coded targets are classified. Moreover, the gray scale centroid algorithm is applied to obtain the subpixel location of both uncoded and coded targets. The initial matching of the uncoded target correspondences between an image pair is established according to similarity and compatibility, which are based on the ID correspondences of the coded targets. The outliers in the initial matching of the uncoded target are eliminated according to three rules to finally obtain the uncoded target correspondences. Practical examples show that the algorithm is rapid, robust and is of high precision and matching ratio.

Outdoor relative radiometric calibration method using gray scale targets

The radiometric calibration of remote sensors is a basis and prerequisite of information quantification in remote sensing. This paper proposes a method for outdoor relative radiometric calibration using gray scale targets. In this method, the idea of two substitutions is adopted. Sunlight is used to replace the integrating sphere light source, and gray scale targets are used to re-place the diffuser. In this way, images at different radiance levels obtained outdoors can calculate the relative radiometric cali-bration coefficients using the least square method. The characteristics of this method are as follows. Firstly, compared with la-boratory calibration, it greatly reduces the complexity of the calibration method and the test cost. Secondly, compared with the existing outdoor relative radiometric calibration of a single radiance level, it uses test images of different radiance levels to re-duce errors. Thirdly, it is easy to operate with fewer environmental requirements, has obvious advantages in the rapid calibra-tion of airborne remote sensors before or after flight and is practical in engineering. This paper theoretically and experimental-ly proves the feasibility of this method. Calibration experiments were conducted on the wide-view multispectral imager (WVMI) using this method, and the precision of this method was evaluated by analyzing the corrected images of large uniform targets on ground. The experiment results have demonstrated that the new method is effective and its precision meets the re-quirement of the absolute radiometric calibration.

A self-driving solution for resource-constrained autonomous vehicles in parked areas

Autonomous vehicles in industrial parks can provide intelligent,efficient,and environmentally friendly transportation services,making them crucial tools for solving internal transportation issues.Considering the characteristics of industrial park scenarios and limited resources,designing and implementing autonomous driving solutions for autonomous vehicles in these areas has become a research hotspot.This paper proposes an efficient autonomous driving solution based on path planning,target recognition,and driving decision-making as its core components.Detailed designs for path planning,lane positioning,driving decision-making,and anti-collision algorithms are presented.Performance analysis and experimental validation of the proposed solution demonstrate its effectiveness in meeting the autonomous driving needs within resource-constrained environments in industrial parks.This solution provides important references for enhancing the performance of autonomous vehicles in these areas.

Maximal admissible mode decision delay in terminal guidance

Mode decision-maker is a critical component in the logic-based Integrated Estimation and Guidance(IEG) system. For the best possible estimation and guidance performance, the mode decision delay of the mode decision-maker should be limited to a range as small as possible. This paper presents a numerical method for computing the maximal admissible mode decision delay that varies with time-to-go. Particular attention has been paid to highly maneuvering target interception in terminal guidance. The results of this research offer useful guidelines for the design of the mode decision-maker in IEG systems.