Operational requirements analysis method based on question answering of WEKG

The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.

Aero-engine Blade Fatigue Analysis Based on Nonlinear Continuum Damage Model Using Neural Networks

Fatigue life and reliability of aero-engine blade are always of important significance to flight safety.The establishment of damage model is one of the key factors in blade fatigue research.Conventional linear Miner＇s sum method is not suitable for aero-engine because of its low accuracy.A back propagation neutral network（BPNN） based on the combination of Levenberg-Marquardt（LM） and finite element method（FEM） is used to describe process of nonlinear damage accumulation behavior in material and predict fatigue life of the blade.Fatigue tests of standard specimen made from TC4 are carried out to obtain material fatigue parameters and S-N curve.A nonlinear continuum damage model（CDM）,based on the BPNN with one hidden layer and ten neurons,is built to investigate the nonlinear damage accumulation behavior,in which the results from the tests are used as training set.Comparing with linear models and previous nonlinear models,BPNN has the lowest calculation error in full load range.It has significant accuracy when the load is below 500 MPa.Especially,when the load is 350 MPa,the calculation error of the BPNN is only 0.4%.The accurate model of the blade is built by using 3D coordinate measurement technology.The loading cycle in fatigue analysis is defined from takeoff to cruise in 10 min,and the load history is obtained from finite element analysis（FEA）.Then the fatigue life of the compressor blade is predicted by using the BPNN model.The final fatigue life of the aero-engine blade is 6.55 104 cycles（10 916 h） based on the BPNN model,which is effective for the virtual design of aero-engine blade.

Novel delay-dependent stability analysis of Takagi-Sugeno fuzzy uncertain neural networks with time varying delays

This paper presents the stability analysis for a class of neural networks with time varying delays that are represented by the Takagi^ugeno IT-S） model. The main results given here focus on the stability criteria using a new Lyapunov functional. New relaxed conditions and new linear matrix inequality-based designs are proposed that outperform the previous results found in the literature. Numerical examples are provided to show that the achieved conditions are less conservative than the existing ones in the literature.

Almost sure exponential stability of neutral stochastic delayed cellular neural networks

In this paper, almost sure exponential stability of neutral delayed cellular neural networks which are in the noised environment is studied by decomposing the state space to sub-regions in view of the saturation linearity of output functions of neurons of the cellular neural networks. Some algebraic criteria are obtained and easily verified. Some examples are given to illustrate the correctness of the results obtained.

Study in Soybean Yield Forecast Application Based on Hopfield ANN Model

Using the artificial nerve network′s knowledge, establish the estimate′s mathematics model of the soybean′s yield, and by the model we can increase accuracy of the soybean yield forecast.

Data fusion of radar and IFF for aircraft identification

The problem of identification of friend-or-foe aircraft in the actual application condition is addressed.A hybrid algorithm combining fuzzy neutral network with probability factor（FNNP）,multi-level fuzzy comprehensive evaluation and the DempsterShafer（D-S） theory is proposed.This hybrid algorithm constructs a complete process from generating the fuzzy database to the final identification,realizes the identification of friend-or-foe automatically if the training samples or expert’s experience can be obtained,and reduces the effect of uncertainties in the process of identification.At the same time,the whole algorithm can update the identification result with the augment of observations.The performance of the proposed algorithm is assessed by simulations.Results show that the proposed algorithm can successfully deduce the aircraft’s identity even if the observations have measurement errors.

Hierarchical structured robust adaptive attitude controller design for reusable launch vehicles

Reentry attitude control for reusable launch vehicles （RLVs） is challenging due to the characters of fast nonlinear dy- namics and large flight envelop. A hierarchical structured attitude control system for an RLV is proposed and an unpowered RLV con- trol model is developed. Then, the hierarchical structured control frame consisting of attitude controller, compound control strategy and control allocation is presented. At the core of the design is a robust adaptive control （RAC） law based on dual loop time-scale separation. A radial basis function neural network （RBFNN） is implemented for compensation of uncertain model dynamics and external disturbances in the inner loop. And then the robust op- timization is applied in the outer loop to guarantee performance robustness. The overall control design frame retains the simplicity in design while simultaneously assuring the adaptive and robust performance. The hierarchical structured robust adaptive con- troller （HSRAC） incorporates flexibility into the design with regard to controller versatility to various reentry mission requirements. Simulation results show that the improved tracking performance is achieved by means of RAC.

Exponential stability analysis for neutral BAM neural networks with time-varying delays and stochastic disturbances

This paper is concerned with the global exponential stability analysis problem for a class of neutral bidi- rectional associative memory （BAM） neural networks with time-varying delays and stochastic disturbances. The stochastic disturbances are described by state-dependent stochastic processes. By utilizing an appropriately constructed Lyapunov- Krasovskii functional （LKF） and some stochastic analysis approaches, novel delay-dependent conditions are established in terms of linear matrix inequalities （LMIs）, which can be easily solved by existing convex optimization techniques. Further- more, the exponential convergence rate can be estimated based on the obtained results. An illustrate example is given to demonstrate the effectiveness of the proposed methods.

Bogdanov–Takens Bifurcation in a Neutral Delayed Hopfield Neural Network with Bidirectional Connection

In this paper,a neutral Hopfield neural network with bidirectional connection is considered.In the first step,by choosing the connection weights as parameters bifurcation,the critical point at which a zero root of multiplicity two occurs in the characteristic equation associated with the linearized system.In the second step,we studied the zeros of a third degree exponential polynomial in order to make sure that except the double zero root,all the other roots of the characteristic equation have real parts that are negative.Moreover,we find the critical values to guarantee the existence of the Bogdanov–Takens bifurcation.In the third step,the normal form is obtained and its dynamical behaviors are studied after the use of the reduction on the center manifold and the theory of the normal form.Furthermore,for the demonstration of our results,we have given a numerical example.