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Many-objective optimization problems (MaOPs) widely exist in industrial and scientific fields, where there are more than 3 objectives that are conflicting with each other (i.e., the improvement of the performance in one objective may lead to the deterioration of the performance of some other objectives). Because of the conflict between objectives, there is no unique optimal solution for MaOPs, but a group of compromise solutions need to be obtained to balance between objectives. As a class of population-based optimization algorithms inspired by biological evolution principles evolutionary algorithms have been proved to be effective in solving MaOPs, and have become one of the research hot spots in the field of multi-objective optimization. In the past 20 years, the research on many-objective evolutionary algorithms (MaOEAs) has made great progress, and a large number of advanced evolutionary methods and evaluation systems have been proposed and improved. In this paper, the research progress of evolutionary many-objective optimization (EMaO) is comprehensively reviewed. Specifically, it includes: (1) Describing the relevant theoretical background of EMaO; (2) Analyzing the problems and challenges faced by evolutionary algorithms in solving MaOPs; (3) Discussing the development of MaOEAs in detail; (4) Summarizing MaOPs and performance indicators in detail; (5) Introducing the visualization tools for high-dimensional objective space; (6) Summarizing the application of MaOEAs in some fields, and (7) Providing suggestions for future research in the domain.

摘要：在全尺寸结构强度试验中，需将原始理论载荷转化为试验实施载荷，载荷处理的结果直接关乎着试验考核的真实性和有效性。传统的载荷处理方法基于载荷等效，载荷处理完成后再对比数值分析结果，这种开环的载荷处理方法遇到复杂结构和载荷时通常效率和精度都大打折扣。提出了一种基于考核目标等效的试验载荷处理方法，将数值仿真分析结合到载荷处理过程中，搭建一种载荷优化设计-试验态分析-考核目标评估的闭环架构，以结构目标响应为评估判据和优化目标，结合灵敏度分析、遗传算法等智能优化算法，搜索试验态载荷最优解，大幅提高了载荷处理的效率和精度。在此基础上，基于MATLAB GUI平台开发了载荷处理软件，模块化地实现了灵敏度分析、载荷-响应矩阵计算、载荷优化设计等功能。将基于考核目标等效的载荷处理方法成功应用到某飞机升降舵结构载荷处理中，实现了试验考核目标响应误差精准控制 Transformation of the original theoretical load into the testing implementation load is necessary in the ground structure strength test， the results of which directly determine the authenticity and validity of the test. The traditional load transacting method compares the numerical analysis results after load transaction based on load equivalent， and the efficiency and accuracy of this open-loop control method are often reduced significantly when encountering complex structures and loads. We propose a testing load transaction method based on the assessment target equivalent, and combine the numerical simulation analysis with the load transacting process. A closed structure of load optimization, testing state simulated analysis and assessment target evaluation is established. The structural target response is taken as the evaluation criterion and optimization objective. Using the sensitivity analysis and genetic algorithm， this method significantly improves the efficiency and accuracy of load transacting. Furthermore， we develop load transacting software based on the MATLAB GUI platform, implementing a variety of functions modularized, such as the sensitivity analysis， load-response matrix calculation, and load optimization design. This method is then applied to the elevator structure load transacting process, realizing precise control of the assessment target error in the load transacting process.

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Supported by: The National Key Research and Development Program of China(2019YFC1511300);The Natural Science Foundation of Chongqing(cstc2019jcyj-msxmX0666);The Natural Science Foundation of Chongqing(cstc2019jcyj-xfkxX0002) Deep learning can improve the effect of signal detection by extracting the inherent characteristics of wireless communication data. To solve the tradeoff between the performance and complexity of MIMO system signal detection, an end-to-end MIMO system signal detection scheme based on deep learning was proposed. The encoder and the decoder based on residual deep neural network replace the transmitter and the receiver of the wireless communication system respectively, and they were trained in an end-to-end manner as a whole. Firstly, the features of the input data were extracted by encoder, then the communication model was established and was sent to the zero forcing detector for preliminary detection. Finally, the detection signal was reconstructed through the decoder. Simulation results show that the proposed detection scheme is superior to the same type of algorithm, and the detection performance is significantly better than that of the MMSE detection algorithm at the expense of a certain time complexity. People's Posts and Telecommunications Press.

Simultaneous localization and mapping (SLAM) has broad application prospects in many fields due to its high energy efficiency and low power consumption. However, there are still some problems in the traditional SLAM system: the key frame in the traditional visual odometer does not contain semantic information, the image information obtained by the mobile robot is relatively single, and the key frame in the actual scene always contains a large number of mismatched points and dynamic points. In response to the above problems, this paper proposes a new idea of semantic SLAM mapping technology. First, in order to find the correct and corresponding feature points, abandon the interference of dynamic points and mismatched points simultaneously, a method for judging the feature state of adjacent frames based on the Lucas-Kanade optical flow method is proposed, and this function is regarded as a new feature. The thread is added to the visual odometry part of ORB-SLAM3 to complete the optimization and improvement of part of the traditional SLAM framework. Secondly, in view of the problem that the image frame obtained by the front-end visual odometer of the traditional SLAM system does not contain any semantic information, the target detection algorithm based on YOLOV4 and the Mask R-CNN semantic segmentation algorithm fused with fully connected conditional random field CRF are used to compare ORB-SLAM3. The key frame image processing of the robot effectively improves the perception of the indoor environment of smart devices such as robots.

Copyright © 2021 The Author(s). The safety of power batteries have always restricted the promotion and development of electric vehicles. The axial compression of batteries is an important issue leading to damage. The safety performance of 18650 lithium-ion battery under axial compression was studied by experiments. The characters of load, voltage and temperature of batteries with state of charge of 60%, 80%, and 100% were discussed, and the failure process of the battery under axial compression was analyzed. It was found that the voltage during the axial compression process showed a unique stepped drop, the maximum load and a sudden temperature increase occurred almost simultaneously; the local groove structure of the positive induced the battery to rupture near the positive. Comparing the batteries in axial compression with the batteries of the radial two-plate compression, it was found that the thermal runaway of power battery in axial compression is weaker than that in radial two-plate compression.

Copyright © 2021 The Author(s). As the most obvious feature of electrocardiogram(ECG), R wave is often used as an important basis to determine other bands of ECG.Aiming at the low recognition rate of existing algorithms, an R-wave recognition algorithm based on empirical wavelet transform and signal structure characteristics is proposed.Firstly, the empirical wavelet transform is used to adaptively segment the spectrum of ECG signal, and the appropriate wavelet filter banks are constructed in the segmentation interval to extract the tightly supported modal components.Then, the spectrum of each extracted modal component is analyzed to find out the corresponding high frequency component of R wave and analyze its structure, so as to realize the accurate positioning of R wave.The simulation results show that the sensitivity, accuracy and positive rate of the proposed algorithm for R-wave recognition of ECG signal are 99.93%, 99.92% and 99.99% respectively, and the algorithm takes only 0.68s with a good recognition effect for R-wave.

With the attention to the world ecology and economy, people are observing the abundant, low-cost, and clean renewable energy from sun and wind. However, most of the renewable energy sources are intermittent and cannot meet the needs for applications, except for converting to electricity. In order to satisfy the demand of people for new energy storage equipment, supercapacitors using biomass-based carbon materials as electrode materials have attracted much attention, because the multi-level structure of the natural biomass material is conducive to ion transmission. The fine structure of natural biomass cannot be synthesized artificially. The preservation of natural multi-scale structure can provide better electrochemical performance of the biomass-based carbon material. The biomass waste of sword beans shell with the characteristics of fast growth, a large amount of sword bean shells can be continuously produced as raw materials every year, but are often discarded or burned, which contributes to the environmental pollution. It is a promising precursor for obtaining hierarchically porous carbon-based material used as active component of high-storage capacity supercapacitors. The activated carbon with high surface area derived from sword shell by using KOH activation method and used as supercapacitor electrode materials. Taking the specific capacitance value of electrode material as the response value, the activation temperature and the activation ratio as the experimental factors, the Central Composite Design (CCD) method was employed to carry out the response surface optimization study, and the electrochemical performance of the activated carbon prepared under the optimal process conditions was explored. The research results show that the activation temperature and activation ratio have significant effects on the specific capacitance of activate carbon material. The coefficient R2 of the model is 97.54%, and the correction coefficient Adj R2 is 95.78%, indicating that the model can better predict the specific capacitance value of sword shell-based activated carbon with high reliability. The specific capacitance can reach a peak value under the condition of activation temperature 700 ℃ and the activation ratio 4∶1. The optimized process parameters determined by center composite design approach were the activation temperature of 694 ℃ and the activation ratio of 4.17∶1. The verification experiment shows that the average specific capacitance of the sword shell activated carbon material is 254 F/g, which is basically consistent with the predicted value. Furthermore, the Cyclic Voltammetry (CV) curves and Galvanostatic Charge-discharge (GCD) curves of different carbon materials were compared. A quasi-rectangular shape with wide hump peaks can be observed in CV curves, which can be attributed to the synergy between the Electric Double-layer Capacitance (EDLC) and the pseudocapacitance. The nitrogen fixation of legumes can provide carbon materials with nitrogen to produce redox reactions and provide pseudocapacitance. The GCD curves show nearly triangular shapes with a small deviation from linearity, which indicated excellent capacitive behavior of the electrode materials. The Nyquist plots from the Electrochemical Impedance Spectroscopy (EIS) analysis reveal that sword shell-based activated carbon has good electronic conductivity. Additionally, the physical properties of activated carbon was characterized. The apparent morphology of activated carbon was observed by Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM). The nitrogen adsorption-desorption was conducted to investigate the pore structure of the carbon material. The results showed that: sword shell-based activated carbons possess a large number of nanopores, which distributed on the surface of the material, and the maximum specific surface area, total pore volume and micropore volume can up to 3 129 m2/g, 1.68 cm3/g and 0.96 cm3/g, which is conducive to electrolyte circulation and electrolyte ion adsorption.