With the development of modern military strategy, satellite observation has become a key asset for obtaining global security and operational environment dynamics. This article proposes an intelligent scheduling method...
详细信息
With the development of modern military strategy, satellite observation has become a key asset for obtaining global security and operational environment dynamics. This article proposes an intelligent scheduling method for ground observation of satellite based on segmented coding, aiming to optimize observation plans, improve the quality and efficiency of data collection. The article first analyzes the current research status of satellite observation duration allocation and points out the shortcomings of current research on ground observation task duration allocation. In response to this issue, this article establishes an observation duration allocation model, which maximizes the observation benefits of satellites in different orbits(high, medium, and low) by adjusting the observation duration decision variables of each satellite. The model introduces an encoding system to represent different observation time allocation schemes and establishes a relationship function between observation duration and benefit value. Furthermore, this article proposes an improved genetic algorithm based on allele replacement to solve the allocation problem of observation time. The experimental results show that the method tends to stabilize after 10000 iterations, and the total allocatable time resource utilization rate of the proposed scheduling scheme reaches 99.9999%, which is much higher than the benefit value of the uniform allocation scheme, proving the feasibility and effectiveness of the proposed method in this paper.
Recently the development of optimization algorithm is rapidly increased. Among several optimization algorithms, Harmony Search (HS) has been recently proposed for solving engineering optimization problems. The HS has ...
详细信息
ISBN:
(纸本)9781450372015
Recently the development of optimization algorithm is rapidly increased. Among several optimization algorithms, Harmony Search (HS) has been recently proposed for solving engineering optimization problems. The HS has some weaknesses such as parameters selection and falling in local optima. Many variants proposed to solve these problems. This paper presents successful hybrid algorithms with high performance to solve the pressure vessel design simulation. The hybrid algorithms consist of well-known variants of HS and an opposition-based learning technique. The hybrid algorithm improved the HS exploration and avoiding falling in local optima, which lead the algorithm to provide significant results.
The traditional model predictive control(MPC) has the problems of heavy computational burden and low predictive *** improved MPC is therefore proposed in this paper via combining the idea of no-beat control to calcu...
详细信息
The traditional model predictive control(MPC) has the problems of heavy computational burden and low predictive *** improved MPC is therefore proposed in this paper via combining the idea of no-beat control to calculate the target reference voltage *** optimizing the voltage vector selection,not only the calculation times of the control algorithm are reduced,but also the load current harmonic content,the inverter switching frequency and the power loss are *** delay compensation is carried out to improve the accuracy of the model prediction,so as to improve the operation efficiency of the grid-connected ***,the improved MPC simulation model is established in MATLAB/SIMULINK and the improved MPC is compared with the traditional MPC to verify its effectiveness in the experimental prototype.
We present a general information theoretic approach for identifying functional subgraphs in complex neuronal networks where the spiking dynamics of a subset of nodes (neurons) are observable. We show that the uncertai...
详细信息
We present a general information theoretic approach for identifying functional subgraphs in complex neuronal networks where the spiking dynamics of a subset of nodes (neurons) are observable. We show that the uncertainty in the state of each node can be written as a sum of information quantities involving a growing number of variables at other nodes. We demonstrate that each term in this sum is generated by successively conditioning mutual information on new measured variables, in a way analogous to a discrete differential calculus. The analogy to a Taylor series suggests efficient optimization algorithms for determining the state of a target variable in terms of functional groups of other nodes. We apply this methodology to electrophysiological recordings of cortical neuronal network grown in vitro. Despite strong stochasticity, we show that each cell's firing is generally explained by the activity of a small number of other neurons. We identify these neuronal subgraphs in terms of their redundant or synergetic character and reconstruct neuronal circuits that account for the state of target cells. [ABSTRACT FROM AUTHOR]
The power system stabilizer can suppress the electromechanical oscillation and enhance the power system stability with the aid of its additional excitation control. The need for power system stabilizations has been in...
详细信息
ISBN:
(纸本)9781457715808;9781457715839
The power system stabilizer can suppress the electromechanical oscillation and enhance the power system stability with the aid of its additional excitation control. The need for power system stabilizations has been increasing day by day. The demand for electric power requirement has motivated the usage of power system in an effective and reliable way. The stability of the power system is the ability to extend restoring forces equal to or greater than the disturbing forces to sustain the state of equilibrium. Power industries are restructured to provide effective utilization to more users at lower prices and better power efficiency. The complexity of the Power systems has been increasing as they become inter-connected. Load demand also increases linearly with the increase in users. Since stability phenomena limits the transfer capability of the system, there is a need to ensure stability and reliability of the power system due to economic reasons. With these conditions, experts and researchers were continually tasked to find simple, effective and economical strategy of attaining stabilization of the power system, which is considered of highest priority. Thus, because of the importance of the stability of the power systems, stabilizing control techniques have been used for the multi-machine power system with the help of intelligent methods. The optimal sequential design for multi-machine power systems is very essential. As a result, serious consideration is now being given on the concern of power system stabilization control. In recent times, the utilization of optimization techniques becomes possible to deal with control signals in power system. This paper uses the Artificial Bee Colony algorithm for better stability of the power system. Simulation results suggest that the proposed technique is better for power system stabilization when compared to the conventional techniques.
This paper addresses the design problem of the distributed optimization algorithms for tracking targets over Wireless Sensor Networks through coordinative communication. To balance the tradeoff between tracking error ...
详细信息
This paper addresses the design problem of the distributed optimization algorithms for tracking targets over Wireless Sensor Networks through coordinative communication. To balance the tradeoff between tracking error and control power consumption, a performance index is established in advance. Then, the optimization algorithm is designed consisting of an error integrator term and a feedforward term which can eliminate the steady-state tracking error and compensate the disturbance effect respectively. Finally, the numerical simulation is performed. By applying the designed control in an Autonomous Underwater Vehicle leader-follower formation control system, the algorithms are validated effective, feasible, and easy to be implemented.
The prediction of security risk is a new problem in the field of *** value of food safety risk is dynamic,non-linear and *** order to improve the prediction accuracy of non-stationary sequences,this paper proposes an ...
详细信息
The prediction of security risk is a new problem in the field of *** value of food safety risk is dynamic,non-linear and *** order to improve the prediction accuracy of non-stationary sequences,this paper proposes an improved time series prediction model of bidirectional long short-term memory network based on NSADAM optimization *** using NS-ADAM optimization algorithm,the non-stationary series can be approximately regarded as stationary series in a fixed window *** with the advantages of two-way long-term and short-term network model to strengthen the correlation between current data and historical data,the combined network model significantly improves the prediction accuracy of non-stationary time *** experimental results show that compared with the traditional integrated moving average autoregressive model and the conventional long-term and short-term memory network model,the improved model has higher prediction accuracy and better fitting effect for non-stationary series.
Cyberbullying has emerged as a serious societal and public health problem that demands accurate methods for the detection of cyberbullying instances in an effort to mitigate the consequences. While techniques to autom...
详细信息
ISBN:
(纸本)9781538646595
Cyberbullying has emerged as a serious societal and public health problem that demands accurate methods for the detection of cyberbullying instances in an effort to mitigate the consequences. While techniques to automatically detect cyberbullying incidents have been developed, the scalability and timeliness of existing cyberbullying detection approaches have largely been ignored. We address this gap by formulating cyberbullying detection as a sequential hypothesis testing problem. Based on this formulation, we propose a novel algorithm designed to reduce the time to raise a cyberbullying alert by drastically reducing the number of feature evaluations necessary for a decision to be made. We demonstrate the effectiveness of our approach using a real-world dataset from Twitter, one of the top five networks with the highest percentage of users reporting cyberbullying instances. We show that our approach is highly scalable while not sacrificing accuracy for scalability.
Backgroud: Constraint-based flux analysis have been widely used in metabolic engineering to predict genetic optimization *** methods seek to find genetic manipulations that maximally couple the desired metabolite with...
详细信息
Backgroud: Constraint-based flux analysis have been widely used in metabolic engineering to predict genetic optimization *** methods seek to find genetic manipulations that maximally couple the desired metabolite with the cellular growth ***, such framework does not work well for overproducing chemicals that are not closely connected with biomass, for example non-native biochemical production by introducing synthetic pathways into heterologous host cells.
In the process of rotation, the total weight of the bridge structure is jointly supported by the spherical hinge and the supporting structure, and its lateral stability is poor. It is easy to lose stability under the ...
详细信息
In the process of rotation, the total weight of the bridge structure is jointly supported by the spherical hinge and the supporting structure, and its lateral stability is poor. It is easy to lose stability under the action of dynamic loads such as seismic action effect. The present paper takes a 10,000-ton continuous rigid frame swivel bridge as the re-search object, analyzes the dynamic response of the seismic action to the horizontal swivel system and establishes several structure simulation models. Eighteen seismic waves in three directions that meet the calculation requirements are screened for time history analysis and compared with the response spectrum method. Finally, an optimization algorithm for the seismic response of the bridge under horizontal swivel system is proposed based on the mode superposition method. The UHPC spherical hinge bears all the vertical forces and 20% of the bending moment caused by the seismic action, the support structure bearing the remaining 80% of the bending moment. The optimization algorithm proposed in this paper features high accuracy.
暂无评论