Research on the Mechanism of Multi-Sensor Fusion Configuration Based on the Optimal Principle of the Vehicle

In order to address the issue of sensor configuration redundancy in intelligent driving,this paper constructs a multi-objective optimization model that considers cost,coverage ability,and perception performance.And then,combining a specific set of parameters,the NSGA-II algorithm is used to solve the multi-objective model established in this paper,and a Pareto front containing 24 typical configuration schemes is extracted after considering empirical constraints.Finally,using the decision preference method proposed in this paper that combines subjective and objective factors,decision scores are calculated and ranked for various configuration schemes from both cost and performance preferences.The research results indicate that the multi-objective optimization model established in this paper can screen and optimize various configuration schemes from the optimal principle of the vehicle,and the optimized configuration schemes can be quantitatively ranked to obtain the decision results for the vehicle under different preference tendencies.

《住宅用综合信息箱技术要求》国家标准正式发布

近期,根据国家标准化管理委员会公告显示,由全国智能建筑及居住区数字化标准化技术委员会(简称'全国智标委')归口,广州智慧家庭技术标准促进中心、杭州鸿雁智能科技有限公司等18家企事业单位共同编制的《住宅用综合信息箱技术要求》(GB/T 37142—2018)国家标准正式发布。

Standardization of CPUE for Chilean Jack Mackerel (Trachurus murphyi) from Chinese Trawl Fleets in the High Seas of the Southeast Pacific Ocean

The generalized linear model （GLM） and generalized additive model （GAM） were applied to the standardization of catch per unit effort （CPUE） for Chilean jack mackerel from Chinese factory trawl fishing fleets in the Southeast Pacific Ocean from 2001 to 2010 by removing the operational, environmental, spatial and temporal impacts. A total of 9 factors were selected to build the GLM and GAM, i.e., Year, Month, Vessel, La Nifia and E1 Nifio events （ELE）, Latitude, Longitude, Sea surface temperature （SST）, SST anomaly （SSTA）, Nino3.4 index and an interaction term between Longitude and Latitude. The first 5 factors were significant components in the GLM, which in combination explained 27.34% of the total variance in nominal CPUE. In the stepwise GAM, all factors explained 30.78% of the total variance, with Month, Year and Vessel as the main factors influencing CPUE. The higher CPUE occurred during the period April to July at a SST range of 12-15℃ and a SSTA range of 0.2-1.0℃. The CPUE was significantly higher in normal years compared with that in La Nifia and E1 Nifio years. The abundance of Chilean jack mackerel declined during 2001 and 2010, with an increase in 2007. This work provided the relative abundance index of Chilean jack mackerel for stock as- sessment by standardizing catch and effort data of Chinese trawl fisheries and examined the influence of temporal, spatial, environ- mental and fisheries operational factors on Chilean jack mackerel CPUE.

Open multilevel hierarchic intelligent control system for eco-industrial system

In allusion to the characteristics of the open complex giant system, an open multilevel hierarchic intelligent control system is established for the eco-industrial system. With the idea of the open engineering system, using the hall for workshop of metasynthetic engineering （HWME）, intelligent control techniques, the expert system and the design of experiments are integrated within the framework of the nonlinear multiobjective decision support system to develop a robust, top-level design specification so as to make the system have the quality of adaptive control, self-organizing, self-learning and robustness. Finally, an illustrative example is given to clarify the effectiveness of the method.

Low energy consumption depth control method of self-sustaining intelligent buoy

Aiming at the contradiction between the depth control accuracy and the energy consumption of the self-sustaining intelligent buoy,a low energy consumption depth control method based on historical array for real-time geostrophic oceanography(Argo)data is proposed.As known from the buoy kinematic model,the volume of the external oil sac only depends on the density and temperature of seawater at hovering depth.Hence,we use historical Argo data to extract the fitting curves of density and temperature,and obtain the relationship between the hovering depth and the volume of the external oil sac.Genetic algorithm is used to carry out the optimal energy consumption motion planning for the depth control process,and the specific motion strategy of depth control process is obtained.Compared with dual closed-loop fuzzy PID control method and radial basis function(RBF)-PID method,the proposed method reduces energy consumption to 1/50 with the same accuracy.Finally,a hardware-in-the-loop simulation system was used to verify this method.When the error caused by fitting curves is not considered,the average error is 2.62 m,the energy consumption is 3.214×10^(4)J,and the error of energy consumption is only 0.65%.It shows the effectiveness and reliability of the method as well as the advantages of comprehensively considering the accuracy and energy consumption.

Depth control for a deep-sea self-holding intelligent buoy system based on active disturbance rejection control method

The net buoyancy of the deep-sea self-holding intelligent buoy(DSIB)will change with depth due to pressure hull deformation in the deep submergence process.The net buoyancy changes will affect the hovering performance of the DSIB.To make the DSIB have better resistance to the external disturbances caused by the net buoyancy and water resistance,a depth controller was designed to improve the depth positioning based on the active disturbance rejection control(ADRC).Firstly,a dynamic model was established based on the motion analysis of the DSIB.In addition,the extended state observer(ESO)and nonlinear state error feedback controller were designed based on the Lyapunov stability principle.Finally,semi-physical simulations for the depth control process were made by using the ADRC depth controller and traditional PID depth controller,respectively.The results of the semi-physical simulations indicate that the depth controller based on the ADRC can achieve the predefined depth control under the external disturbances.Compared with the traditional PID depth controller,the overshoot of the ADRC depth controller is 1.74%,and the depth error is within 0.5%.It not only has a better control capability to restrain the overshoot and shock caused by the external disturbances,but also can improve intelligence of the DSIB under the depth tracking task.

Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.

An Overview of Smart City in China

The year of 2013 is considered the first year of smart city in China. With the development of informationization and urbanization in China, city diseases(traffic jam, medical problem and unbalanced education) are more and more apparent. Smart city is the key to solving these diseases. This paper presents the overall smart city development in China in term of market scale and development stages, the technology standards, and industry layout. The paper claims that the issues and challenges facing smart city development in China and proposes to make polices to support smart city development.

SGCC Smart Grid Standardization

This paper introduces the progress of State Grid Corporation of China （SGCC） in smart grid standardization, including the smart grid standards system, standards reversion and development, the role of standards system in smart grid demonstration projects, and the situation of SGCC participation in both domestic and international smart grid standardization work.

A Sensor-Service Collaboration Approach for Target Tracking in Wireless Camera Networks

Mobile target tracking is a necessary function of some emerging application domains, such as virtual reality, smart home and intelligent healthcare. However, existing portable devices for target tracking are resource intensive and high-cost. Camera tracking is an effective location tracking way for those emerging applications which can reuse the existing ubiquitous video monitoring system. This paper proposes a dynamic community-based camera collaboration(D3C) framework for target location and tracking. The contributions of D3C mainly include that(1) nonlinear perspective projection model is selected as the camera sensing model and sequential Monte Carlo is employed to predict the target location;(2) a dynamic collaboration scheme is proposed, it is based on the local community-detection theory deriving from social network analysis. The performance of proposed approach is validated by both synthetic datasets and real-world application. The experiment results show that D3C meets the versatility, real-time and fault tolerance requirements of target tracking applications.

Risk Identif ication and Prevention to the Intelligent Network Implementation

Risk management are set of processes which include risk identification, risk analysis, risk evaluation and risk implementation. Risk exists throughout the entire life cycle of the project. It is an important guarantee for the success of the project to establish a good risk management mechanism and the risk-based decision-making mechanism. Personal communication tries to connect various telecommunication services to people, one of the key technologies to realise personal communication is to establish an advanced intelligent network—a kind of communication network that can provide and deal with the intelligent new businesses. It is an important guarantee for the success of the project to establish a good risk management mechanism and the risk-based decision-making mechanism.

AN ADAPTIVE MOVING TARGET TRACKING ALGORITHM FOR SMART ANTENNA SYSTEMS

In wireless communication environment, the time-varying channel and angular spreads caused by multipath fading and the mobility of Mobile Stations (MS) degrade the performance of the conventional Direction-Of-Arrival (DOA) tracking algorithms. On the other hand, although the DOA estimation methods based on the Maximum Likelihood (ML) principle have higher resolution than the beamforming and the subspace based methods, prohibitively heavy computation limits their practical applications. This letter first proposes a new suboptimal DOA estimation algorithm that combines the advantages of the lower complexity of subspace algorithm and the high accuracy of ML based algo- rithms, and then proposes a Kalman filtering based tracking algorithm to model the dynamic property of directional changes for mobile terminals in such a way that the association between the estimates made at different time points is maintained. At each stage during tracking process, the current suboptimal estimates of DOA are treated as measurements, predicted and updated via a Kalman state equation, hence adaptive tracking of moving MS can be carried out without the need to perform unduly heavy computations. Computer simulation results show that this proposed algorithm has better per- formance of DOA estimation and tracking of MS than the conventional ML or subspace based algo- rithms in terms of accuracy and robustness.

Intelligent Control Plane Techniques for Next Generation Optical Switching Networks

For the next generation optical switching networks, the intelligent control plane is a key enabling technique. In this paper, we review our recent research activities related to Generalized Multi-Protocol Label Switching (GMPLS) and Open Flow-based control planes for both Wave length Switched Optical Networks (WSON) and Elastic Optical Networks (EON).

Method of Dynamic Optimal Rout Calculation in the ＂Smart Clean City＂ Project

A solution of the optimization garbage removal problem in the large cities is suggested. In this paper there is described a system architecture to find time-optimal dynamic route for garbage trucks within ＂Smart Clean City＂ project which unites an approach to put special electronic devices on the garbage containers with the developed software responsible for the detecting the filled up containers and building the optimal way to collect the garbage. There is proposed a formal mathematical model of the task of dynamic optimal route and formal the optimization criterion for time-optimal garbage collection of all waste from landfills. The system includes the knowledge base which contains the rule describing the expert knowledge of the city traffic situation.

Dyna-QUF:Dyna-Q based univector field navigation for autonomous mobile robots in unknown environments

A novel approach was presented to solve the navigation problem of autonomous mobile robots in unknown environments with dense obstacles based on a univector field method. In an obstacle-free environment, a robot is ensured to reach the goal position with the desired posture by following the univector field. Contrariwise, the univector field cannot guarantee that the robot will avoid obstacles in environments. In order to create an intelligent mobile robot being able to perform the obstacle avoidance task while following the univector field, Dyna-Q algorithm is developed to train the robot in learning moving directions to attain a collision-free path for its navigation. Simulations on the computer as well as experiments on the real world prove that the proposed algorithm is efficient for training the robot in reaching the goal position with the desired final orientation.

Smart Human Computer Interface with EMG and Vision Based on Multi-modal Information Fusion

A smart Human Interface （HCI） replacing conventional mouse interface is proposed. The interface is able to control and command action with only hand. Four finger motions （left click, right dick, hold, drag） are used to command the interface. Also the authors materialiae cursor movement control using image processing The measure what they use for inference is entropy of Electromyogram （EMG） signal, Gaussian modeling and likelihood estimation. In image processing for cursor control, they use color recognition to get the center point of finger tip from marker, and map the point onto cursor. Accuracy of finger movement inference is over 95% and cursor control works naturally without delay. They materlalize whole system to check its performance and utility.

Research of database-based modeling for mining management system

Put forward the method to construct the simulation model automatically with database-based automatic modeling(DBAM) for mining system. Designed the standard simulation model linked with some open cut Pautomobile dispatch system. Analyzed and finded out the law among them, and designed model maker to realize the automatic pro- gramming of the new model program.

A Research and Design on Application of Genetic Algorithm

Traditional algorithms of intelligent test paper generation have some shortcomings of slow generating speed, low success probability and poor generating quality. Genetic Algorithm is a random optimization-searching algorithm based on probability. In this paper, based on the user＇ s request of intelligent test paper generation, we establish the mathematical model and object function, and give some improvements in Simple GA for test paper generation. Based on the algorithm, a automatic generating test paper system is designed and implemented.

Key problems in validation of intelligent models

To provide a realistic simulation environment for users,intelligent models have become key components in military simulations. After the analysis of modeling nature of intelligent models,the validation criteria for defining the validation points and validation metrics for measuring the agreements between human experts and intelligent models were presented. Further,such methods as graphical comparison,feature analysis and face validation were discussed according to the characteristics of intelligent models. Based on the validation criteria,validation metrics and validation methods,the intelligent models can be effectively validated,which has been proved in current developed intelligent models.

A multi-objective optimization framework for ill-posed inverse problems

Many image inverse problems are ill-posed for no unique solutions. Most of them have incommensurable or mixed-type objectives. In this study, a multi-objective optimization framework is introduced to model such ill-posed inverse problems. The conflicting objectives are designed according to the properties of ill-posedness and certain techniques. Multi-objective evolutionary algorithms have capability to optimize multiple objectives simultaneously and obtain a set of trade-off solutions. For that reason, we use multi-objective evolutionary algorithms to keep the trade-off between these objectives for image ill-posed problems. Two case studies of sparse reconstruction and change detection are imple- mented. In the case study of sparse reconstruction, the measurement error term and the sparsity term are optimized by multi-objective evolutionary algorithms, which aims at balancing the trade-off between enforcing sparsity and reducing measurement error. In the case study of image change detection, two conflicting objectives are constructed to keep the trade-off between robustness to noise and preserving the image details. Experimental results of the two case studies confirm the multi-objective optimization framework for ill-posed inverse problems in image processing is effective.