Fast solution to the free return orbit's reachable domain of the manned lunar mission by deep neural network

It is important to calculate the reachable domain(RD)of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft. In this paper, the RD of free return orbits is quickly evaluated and calculated via the classification and regression neural networks. An efficient databasegeneration method is developed for obtaining eight types of free return orbits and then the RD is defined by the orbit’s inclination and right ascension of ascending node(RAAN) at the perilune. A classify neural network and a regression network are trained respectively. The former is built for classifying the type of the RD, and the latter is built for calculating the inclination and RAAN of the RD. The simulation results show that two neural networks are well trained. The classification model has an accuracy of more than 99% and the mean square error of the regression model is less than 0.01°on the test set. Moreover, a serial strategy is proposed to combine the two surrogate models and a recognition tool is built to evaluate whether a lunar site could be reached. The proposed deep learning method shows the superiority in computation efficiency compared with the traditional double two-body model.

Multi-Resources Management in 6G-Oriented Terrestrial-Satellite Network

The six-generation(6G)wireless network is expected to satisfy the requirements of ubiquitous connectivity and intelligent endogenous.Terrestrialsatellite networks(TSN)enable seamless coverage for terrestrial users in a wide area,making it very promising in 6G.As data traffic in TSNs surges,the integrated management for caching,computing,and communication(3C)has attracted much research attention.In this paper,we investigate the multi-resource management in the uplink and downlink transmission of TSN,respectively.In particularly,we aim to guarantee both throughput fairness and data security in the uplink transmission of TSN.Considering the intermittent communication of the satellite,we introduce two kinds of relays,i.e.,terrestrial relays(TRs)and aerial relays(ARs)to improve the system throughput performance in the downlink transmission of TSN.Finally,we study a specific case of TSN with the uplink and downlink transmission,and the corresponding simulation results validate the effectiveness of our proposed schemes.

Determination of Weak Points Based on Risk Theory and Application to Transmission Network Planning

In the traditional power transmission network planning,deterministic analysis methods are widely used.In such methods,all contingencies are deemed to have the same occurrence probability,which is not reasonable.In this paper,risk assessment is introduced to the process of transmission network planning considering the probabilistic characteristics of contingencies.Risk indices are given to determine the weak points of the transmission network based on local information,such as bus risk,line overload risk,contingency severity.The indices are calculated by the optimal cost control method based on risk theory,which can help planners to quickly determine weak points in the planning and find solution to them.For simplification,only line overload violation is considered.Finally,the proposed method is validated by an IEEE-RTS test system and a real power system in China from two aspects.In the first case,the original system is evaluated by the proposed method to find the weak points,and then four planning schemes are established,among which the best scheme is selected.In the second case,four initial planning schemes are established by combining the experiences of planners,and after the evaluation by using the proposed method,the best planning scheme is improved based on the information of weak points in the initial schemes,and the risk of improved scheme is reduced from 42 531.86 MW·h per year to 4 431.26 MW·h per year.

Reconstructing early transmission networks of SARS-CoV-2 using a genomic mutation model

The coronavirus disease 2019(COVID-19)pandemic has greatly damaged human society,but the origins and early transmission patterns of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)pathogen remain unclear.Here,we reconstructed the transmission networks of SARS-CoV-2 during the first three and six months since its first report based on ancestor-offspring relationships using BANAL-52-referenced mutations.We explored the position(i.e.,root,middle,or tip)of early detected samples in the evolutionary tree of SARS-CoV-2.In total,6799 transmission chains and 1766 transmission networks were reconstructed,with chain lengths ranging from 1-9 nodes.The root node samples of the 1766 transmission networks were from 58 countries or regions and showed no common ancestor,indicating the occurrence of many independent or parallel transmissions of SARS-CoV-2 when first detected(i.e.,all samples were located at the tip position of the evolutionary tree).No root node sample was found in any sample(n=31,all from the Chinese mainland)collected in the first 15 days from 24 December 2019.Results using six-month data or RaTG13-referenced mutation data were similar.The reconstruction method was verified using a simulation approach.Our results suggest that SARS-CoV-2 may have already been spreading independently worldwide before the outbreak of COVID-19 in Wuhan,China.Thus,a comprehensive global survey of human and animal samples is essential to explore the origins of SARS-CoV-2 and its natural reservoirs and hosts.

Particle Swarm Optimization and Its Application in Transmission Network Expansion Planning

The author introduced particle swarm optimization as a new method for power transmission network expansion planning. A new discrete method for particle swarm optimization was developed,which is suitable for power transmission network expansion planning, and requires less computer s memory.The optimization fitness function construction, parameter selection, convergence judgement, and their characters were analyzod.Numerical simulation demonstrated the effectiveness and correctness or the method. This paper provides an academic and practical basis of particle swarm optimization in application of transmission network expansion planning for further investigation.

A Nodal Electricity Market Design Based on Regulated Access to Transmission Network

Accomodation of power system constraints with the market mechanism is encountered as a major challenge along the way toward implementation of different electricity market designs. Allocation of fixe or flow-dependent inter-zone trading capacities by the PX （power exchange） can not be accepted unreservedly. The paper is meant to show that a nodal electricity market design that is based on bids for local energy and a regulated transmission access including allocation of ＂entry-exit＂ transmission capacity would be the desired solution. The market players could easily optimize their portfolio while the TSOs （transmission system operators） are requested to mobilize the network＇s in-built flexibility to increase the cross zonal capacity. In the proposed market design, the PX＇s allocation of trading capacity is clearly separate from the TSO＇s management of the power system operational constraint5. Clear operator roles would enlarge access to electricity market as well as market integration of variable RESs （renewable energy sources） that are critically dependent on short notice access to regionat markets,

Optimum Sizing and Siting of an Embedded Solar Photovoltaic Generation: A Case Study of 33 kv Sub-Transmission Network at Tarkwa, Ghana

The interconnection of Solar PV to the Tarkwa Bulk Supply Point (BSP) has become necessary in order to provide additional capacity to meet the ever-increasing demand of Tarkwa and its environs during the day. The Solar PV Plant will support the Tarkwa BSP during the day. In this study, a grid impact analysis for the integration of Solar PV plant at three points of common coupling (PCC) at Tarkwa Bulk Supply Point’s (BSP) 33 kV network of the Electricity Company of Ghana was carried out. The three PCCs were Tarkwa BSP, Ghana Australia Gold (GAG) Substation and Darmang Substation. Simulations and detailed analysis were carried out with the use of CYME Software (Cyme 8.0 Rev 05). The Solar PV was integrated at varying penetration levels of 9 MWp, 11 MWp, 14 MWp, 16 MWp, 18 MWp, 20 MWp and 23 MWp (representing penetration levels of 40%, 50%, 60%, 70%, 80%, 90% and 100%, respectively) of the 2020 projected light demand of Tarkwa BSP 25.15 MVA network at an average power factor of 0.903. From the study, the optimum capacity of Solar PV power that could be connected is 9 MWp at an optimum inverter power factor of 0.94 lagging, and the GAG Substation was identified as the optimal location. The stiffness ratio at the optimal location was determined as 41.9, a figure which is far greater than the minimum standard value of 5, and gives an indication of very little voltage control problems in the operation of the proposed Solar PV interconnection. The integration of the optimum 9 MW Solar PV Plant to the Tarkwa network represents an additional 12.77% capacity, decreased the technical losses by 7.76%, and increased the voltage profile by 1.97%.

A hybrid particle swarm optimization approach with neural network and set pair analysis for transmission network planning

Transmission network planning (TNP) is a large-scale, complex, with more non-linear discrete variables and the multi-objective constrained optimization problem. In the optimization process, the line investment, network reliability and the network loss are the main objective of transmission network planning. Combined with set pair analysis (SPA), particle swarm optimization (PSO), neural network (NN), a hybrid particle swarm optimization model was established with neural network and set pair analysis for transmission network planning (HPNS). Firstly, the contact degree of set pair analysis was introduced, the traditional goal set was converted into the collection of the three indicators including the identity degree, difference agree and contrary degree. On this bases, using shi(H), the three objective optimization problem was converted into single objective optimization problem. Secondly, using the fast and efficient search capabilities of PSO, the transmission network planning model based on set pair analysis was optimized. In the process of optimization, by improving the BP neural network constantly training so that the value of the fitness function of PSO becomes smaller in order to obtain the optimization program fitting the three objectives better. Finally, compared HPNS with PSO algorithm and the classic genetic algorithm, HPNS increased about 23% efficiency than THA, raised about 3.7% than PSO and improved about 2.96% than GA.

Adaptive Neural Network Control with Control Allocation for A Manned Submersible in Deep Sea

This paper thoroughly studies a control system with control allocation for a manned submersible in deep sea being developed in China. The proposed control system consists of a neural-network-based direct adaptive controller and a dynamic control allocation module. A control energy cost function is used as the optimization criteria of the control allocation module, and weighted pseudo-inverse is used to find the solution of the control allocation problem. In the presence of bounded unknown disturbance and neural networks approximation error, stability of the closed-loop control system of manned submersible is proved with Lyaponov theory. The feasibility and validity of the proposed control system is further verified through experiments conducted on a semi-physical simulation platform for the manned submersible in deep sea.

Modeling and Statistical Properties Research on Online Real-Time Information Transmission Network

In this paper, the model of the online real-time information transmission network, such as wechat, micro-blog, and QQ network, is proposed and built, based on the connection properties between users of the online real-time information transmission network, and combined with the local world evolving characteristics in complex network, then the statistical topological properties of the network is obtained by numerical simulation. Furthermore, we simulated the process of information transmission on the network, according to the actual characteristics of the online real-time information transmission. Statistics show that the degree distribution presents the characteristics of scale free network, presenting power law distribution, while the average path length, the average clustering coefficient and the average size of the network also has a power-law relationship, moreover, the model parameters has no effect on power-law exponent. The spread of information on the network represents obvious fluctuation scaling, reflecting the characteristics that information transmission fluctuates over time.

Improving Mobility Management for All-IP Radio Heterogeneous Network Using SCTP

Mobility management is a very important function of mobile communication in all-IP radio heterogeneous network. In order to achieve an efficient mobility management, with low delay and low beacon overhead, a micro-mobile stream control transmission protocol (mmSCTP) scheme was proposed. This scheme reasonably utilizes SCTP features and elaborately designs execution-steps for vertical handoff. Moreover, it provides fast locating for idle mobile node when a session is initiated by the correspondent node. The analytical and simulation results show that the proposed scheme is effective in supporting fast vertical handoff and effective location management.

Minimum Load-curtailment in Transmission Network Planning Considering Integrated Wind Farms

提出应用鲁棒线性优化理论来研究电网规划中含多个风电场的最小切负荷量计算问题,为含多个风电场的系统安全性研究提供了一条新的思路。根据Seng-Cheol Kang提出的鲁棒线性优化理论,建立电网规划中考虑风电场影响的最小切负荷量模型。该模型以出力上下限和出力期望值来描述风电场的出力,最终转化为一确定性的线性规划问题并进行求解。在计及或不计及发电机调整的情况下,该模型均能够给出最安全的切负荷方案,除此以外还能给出更多介于最可靠与最经济之间的切负荷方案,实现灵活决策;在计及发电机出力可调的情况下,该模型能够给出相应的发电机出力方案;该模型能够初步给出各种切负荷方案下电网规划方案的可靠程度。基于修正的Garver’s 6节点系统和修正的巴西南部46节点系统算例测试结果验证了该方法的有效性。

THE TRANSMISSION CAPACITY OF MANET BASED ON CONFLICT GRAPH

The transmission capacity of Mobile Ad Hoc Networking (MANET) is constrained by the mutual interference of concurrent transmissions between nodes. First, the transmission capacity of MANET is studied by the view of information flow between nodes. At the same time, the problem that the interference between nodes affects the transmission capacity of MANET is also studied by the tool of the event conflict graph. Secondly, the paper presents the method to compute the maximum ex- pectant achievable capacity for the given conflict graph, and concludes and proves an sufficient con- dition that the information flow transmit successfully between nodes. At last, the results are simulated and a fitting equation of transmission capacity between nodes is given.

Energy-Conserving Transmission Network Model Based on Service-Awareness

In this paper, we propose a service-aware network model which is based on the traffic pattern in data center. First of all, we analyze the traffic model in data center networks. Then we use this model to make the net topology integration and classification through the software define network. In order to achieve the purpose of energy consumption optimization, we divide the hosts into same VLAN according to their interaction frequency to reduce the cross VLAN transmission consumption. Simulation results show that we get a great energy improvement in the fat tree net topology.

Reducing the Short Circuit Levels in Kuwait Transmission Network

This paper describes the study analysis performed to evaluate the available and potential solutions to control the highly increasing short circuit （SC） levels in Kuwait power system. The real Kuwait High Voltage （HV） network was simulated to examine different measures at both 275 kV and 132 kV stations. The simulation results show that the short circuit currents exceed the permissible levels （40 kA in the 132 kV network and 63 kA in the 275 kV network） in some specific points. The examined measures include the a study on changing the neutral point policy, changing some lines from alternating current （AC） to direct current （DC）, dividing specific bus bars in some generating stations and applying current limiters. The paper also presents a new plan for the transmission network in order to manage the expected increase in short circuit levels in the future.

改进的DQDB MAN网络性能分析

对比分析了ＤＱＤＢ协议与改进的ＤＱＤＢ协议——具有时隙重用功能和抢占优先功能的、多请求多优先级ＢＷＢ计数器的媒质接入控制机制．分析表明，这种新方法在保持原协议特点的同时，进一步改善了网络带宽分配的性能：时隙重用使网络的吞吐率提高了近１倍；在多优先级网络中ＭＰＢＷＢ机制大大改善了高优先级业务的性能；抢占优先机制使得高优先级业务的性能不受低优先级业务的影响；发送请求窗口值则决定了暂态时间的长短，当它与ＢＷＢ－ＭＯＤ的比值相等时。

Novel multipath routing protocol integrated with forward error correction in MANET

In order to improve the data transmission reliability of mobile ad hoc network, a routing scheme called integrated forward error correction multipath routing protocol was proposed, which integrates the techniques of packet fragmenting and forward error correction encoding into multipath routing. The scheme works as follows: adding a certain redundancy into the original packets; fragmenting the resulting packets into exclusive blocks of the same size; encoding with the forward error correction technique, and then sending them to the destination node. When the receiving end receives a certain amount of information blocks, the original information will be recovered even with partial loss. The performance of the scheme was evaluated using OPNET modeler. The experimental results show that with the method the average transmission delay is decreased by 20% and the transmission reliability is increased by 30%.

FOUR-PARAMETER AUTOMATIC TRANSMISSION TECHNOLOGY FOR CONSTRUCTION VEHICLE BASED ON ELMAN RECURSIVE NEURAL NETWORK

From the viewpoint of energy saving and improving transmission efficiency, the ZL50E wheel loader is taken as the study object. And the system model is analyzed based on the transmission system of the construction vehicle. A new four-parameter shift schedule is presented, which can keep the torque converter working in the high efficiency area. The control algorithm based on the Elman recursive neural network is applied, and four-parameter control system is developed which is based on industrial computer. The system is used to collect data accurately and control 4D180 power-shift gearbox of ZL50E wheel loader shift timely. An experiment is done on automatic transmission test-bed, and the result indicates that the control system could reliably and safely work and improve the efficiency of hydraulic torque converter. Four-parameter shift strategy that takes into account the power consuming of the working pump has important operating significance and reflects the actual working status of construction vehicle.

A Novel Fractional Dengue Transmission Model in the Presence of Wolbachia Using Stochastic Based Artificial Neural Network

The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model(FDTM)in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network(LM-NN)technique.The fractional dengue transmission model(FDTM)consists of 12 compartments.The human population is divided into four compartments;susceptible humans(S_(h)),exposed humans(E_(h)),infectious humans(I_(h)),and recovered humans(R_(h)).Wolbachia-infected and Wolbachia-uninfected mosquito population is also divided into four compartments:aquatic(eggs,larvae,pupae),susceptible,exposed,and infectious.We investigated three different cases of vertical transmission probability(η),namely when Wolbachia-free mosquitoes persist only(η=0.6),when both types of mosquitoes persist(η=0.8),and when Wolbachia-carrying mosquitoes persist only(η=1).The objective of this study is to investigate the effectiveness of Wolbachia in reducing dengue and presenting the numerical results by using the stochastic structure LM-NN approach with 10 hidden layers of neurons for three different cases of the fractional order derivatives(α=0.4,0.6,0.8).LM-NN approach includes a training,validation,and testing procedure to minimize the mean square error(MSE)values using the reference dataset(obtained by solving the model using the Adams-Bashforth-Moulton method(ABM).The distribution of data is 80% data for training,10% for validation,and,10% for testing purpose)results.A comprehensive investigation is accessible to observe the competence,precision,capacity,and efficiency of the suggested LM-NN approach by executing the MSE,state transitions findings,and regression analysis.The effectiveness of the LM-NN approach for solving the FDTM is demonstrated by the overlap of the findings with trustworthy measures,which achieves a precision of up to 10^(-4).