International Journal of Modeling, Simulation, and Scientific Computing

Understanding is the essence of any intelligent system. We revise our four machine understanding paradigms which are: (i) basic understanding, (ii) rich understanding, (iii) exploratory understanding, and (iv) theory-based understanding; and we elaborate on the first two of them. We then introduce the concept of two-stage (or deep) machine understanding which provides descriptive understandings, as well as evaluations of these understandings. After a brief systematization of emotions, we cover the following paradigms for agents with two-stage (deep) understanding abilities for emotional intelligence simulation: (i) basic understanding, (ii) rich-understanding, and (iii) switchable understanding.

On the basis of expert questionnaire and the relevant specification, multi-factors influencing weight matrix was constructed by Analytic Hierarchy Process (AHP) improved in transfer matrix algorithm, and influential factors were fuzzy classified to construct the fuzzy evaluation matrix by using trapezoidal fuzzy membership function. Fuzzy evaluation analysis was carried out through multistage fuzzy comprehensive evaluation method, and verified in combination with engineering construction condition of shallow buried tunnel with large span of Zhongshan Park Station in Qingdao Metro, and four kinds of risk control schemes were established and compared on the analysis of tunnel construction risk. Results show that the model was feasible and the improved construction scheme was very effective to reduce the construction risk.

The comparative study on seven equation models with two different six equations model for compressible two-phase flow analysis is proposed. The seven equations model is derived for compressible two-phase flow that is in the nonconservation form. In the present work, two different six equations model are derived for two pressures, two velocities and single temperature with the derivation of the equation of state. The closing equation for one of the six equations model is energy conservation equation while another one is closed by entropy balance equation. The partial differential form of governing equations is hyperbolic and written in the conservative form. At this point, the set of governing equations are derived based on the principle of extended thermodynamics. The method of solving single temperature from both six equation models are simple and direct solution can be obtained. Numerical simulation has been tried using one of the six equation models for air–water shock tube problems. Explicit fourth order Runge–Kutta scheme is used with Finite Volume Shock Capturing method for solving the governing equations numerically. The pressure, velocity and volume fraction variations are captured along the shock tube length through flow solver. Experimental work is carried out to magnify the initial stage of liquid injection into a gas. The outcome of six equations model for compressible two-phase flow has revealed the multi-phase flow characteristics that are similar to the actual conditions.

In order to further improve the tracking performances of the conventional disturbance observer (DOB)-based control schemes, a dual-loop robust control scheme is proposed for DC electro-mechanical servo system. The outer-loop sliding mode controller (SMC) is designed in order to deal with the impacts from the remainder equivalent disturbances, which is due to the inadequate estimation of the inner-loop DOB. Meanwhile, the existence of DOB can reduce the switching gain of SMC law, which can suppress the high-frequency chattering of control input to a certain extent. Moreover, an approximate differential method is employed in order to reliably acquire the differential information in a noisy environment. From the experiment results on a DC motor servo system, it is presented that the proposed dual-loop control scheme can effectively improve the tracking performances with respect to higher tracking accuracy and stronger system robustness against external disturbances and parameter perturbations, compared with the traditional DOB+PD control scheme.

This paper introduces a CPS application for intelligent aeroplane assembly. At first, the CPS structure is presented, which acquires the characteristics of general CPS and enables "simulation-based planning and control" to achieve high level intelligent assembly. Then the paper puts forward data fusion estimation algorithm under synchronous and asynchronous sampling, respectively. The experiment shows that global optimal distributed fusion estimation under synchronized sampling proves to be closer to the actual value compared with ordinary weighted estimation, and multi-scale distributed fusion estimation algorithm of wavelet under asynchronous sampling does not need time registration, it can also directly link to data, and the error is smaller. This paper presents hybrid control strategy under the circumstance of joint action of the inner and outer loop to address the problems caused by the less controllable feature of the parallel mechanism when undertaking online process simulation and control. A robust adaptive sliding mode controller is designed based on disturbance observer to restrain inner interference and maintain robustness. At the same time, an outer collaborative trajectory planning is also designed. All the experiment results show the feasibility of above proposed methods.

Congestion control is among primary topics in computer network in which random early detection (RED) method is one of its common techniques. Nevertheless, RED suffers from drawbacks in particular when its "average queue length" is set below the buffer's "minimum threshold" position which makes the router buffer quickly overflow. To deal with this issue, this paper proposes two discrete-time queue analytical models that aim to utilize an instant queue length parameter as a congestion measure. This assigns mean queue length (mql) and average queueing delay smaller values than those for RED and eventually reduces buffers overflow. A comparison between RED and the proposed analytical models was conducted to identify the model that offers better performance. The proposed models outperform the classic RED in regards to mql and average queueing delay measures when congestion exists. This work also compares one of the proposed models (RED-Linear) with another analytical model named threshold-based linear reduction of arrival rate (TLRAR). The results of the mql, average queueing delay and the probability of packet loss for TLRAR are deteriorated when heavy congestion occurs, whereas, the results of our RED-Linear were not impacted and this shows superiority of our model.

In the simulation output analysis, there are some measures that should be calculated by time average concept such as the mean queue length. Especially, the confidence interval of those measures might be required for statistical analysis. In this situation, the traditional method that utilizes the central limit theorem (CLT) is inapplicable if the output data set has autocorrelation structure. The bootstrap is one of the most suitable methods which can reflect the autocorrelated phenomena in statistical analysis. Therefore, the confidence interval for a time averaged measure having autocorrelation structure can also be calculated by the bootstrap methods. This study introduces the method that constructs these confidence intervals applying the bootstraps. The bootstraps proposed are the threshold bootstrap (TB), the moving block bootstrap (MBB) and stationary bootstrap (SB). Finally, some numerical examples will be provided for verification.

In this paper, we develop a conceptual framework of a innovation diffusion dynamics model in which multiple parallel innovations are effecting each other during the diffusion process. A mathematical model is proposed to explore the interaction and diffusion of three innovations simultaneously available in market. The stability analysis is carried out for various types of diffusions on such system both analytically and numerically. It is observed that the association between innovations in product market could be complementary, substitute, independent or competitive. The co-existence and extinction of innovation depends on the level of diffusion between the innovations and it may or may not be sensitive to initial distribution of innovations.

Since dozens years ago, various metaheuristic methods, such as genetic algorithm, ant colony algorithms, have been successfully applied to combinational optimization problem. However, as one of the members, ITO algorithm has only been employed in continuous optimization, it needs further design for combinational optimization problem. In this paper, a discrete ITO algorithm inspired by ITO stochastic process is proposed for travelling salesman problems (TSPs). Some key operators, such as move operator, wave operator, are redesigned to adapt to combinational optimization. Moreover, the performance of ITO algorithm in different parameter selections and the maintenance of population diversity information are also studied. By combining local search methods (such as 2-opt and LK-opt) with ITO algorithm, our computational results of the TSP problems show that ITO algorithm is currently one of the best-performing algorithms for these problems.

Electronic warfare simulation can allow the realistic evaluation of the performance of equipments and techniques, and it can also allow the realistic training of individuals under conditions that, in real life, might kill them. We propose a new scheme of EW simulation system based on SystemVue. This paper mainly expounds the structure of system and the key technology of subsystem establishment. As a proof of concept, a radar electronic reconnaissance simulation experiment is explained in this paper. And the results verify the feasibility of the scheme.

Planetary gear trains are widely applied in various transmission units. Whether strengths of all gears are accurately calculated or not can affect reliability of the entire system significantly. Strength calculation method for planetary gear trains usually follows the method for cylindrical gears, in which the worst meshing positions for both contact stress and bending stress cannot be determined precisely, and calculation results tend to be conservative. To overcome these shortcomings, a kinematics analysis for a planetary gear train is firstly performed, in which the influence of relative speed is investigated. Then the finite element strength analysis of a planetary gear train based on its transient meshing properties is carried out in ANSYS. Time–history curves of contact and bending stresses of sun gear, planetary gears and ring gear are respectively obtained. Also the accurate moment and its corresponding position of the maximum stress are precisely determined. Finally, calculation results of finite element method (FEM) and traditional method are compared in order to verify the effectiveness. Simulation and comparison show the stability of the proposed method in this paper. Researches in this paper establish the foundations for fatigue analysis and optimization for a planetary gear train.