In view of the bad forecasting results of the standard epsiv-support vector machine (SVM) for product sale series with the normal distribution noise, a SVM based on the Gaussian loss function named by g-SVM is propose...
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In view of the bad forecasting results of the standard epsiv-support vector machine (SVM) for product sale series with the normal distribution noise, a SVM based on the Gaussian loss function named by g-SVM is proposed. And then, a hybrid forecasting model for product sales and its parameter-choosing algorithm are presented. The results of its application to car sale forecasting indicate that the short-term forecasting method based on g-SVM is effective and feasible.
Aiming at the product demand series with multidimension, small samples, nonlinearity and multi-apex in manufacturing enterprise, chaos theory is combined with support vector machine, and a kind of chaotic support vect...
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Aiming at the product demand series with multidimension, small samples, nonlinearity and multi-apex in manufacturing enterprise, chaos theory is combined with support vector machine, and a kind of chaotic support vector machine named C v -SVM is proposed. And then, a product demand forecasting method and its relevant parameter-choosing algorithm are put forward. The results of application in car demand forecasting show that the forecasting method based on C v -SVM is effective and feasible.
Based on the finite automata theory, a thinking of distributed deadlock supervisor is proposed to avoid deadlock in Knowledgeable Manufacturing systems, which is insensitive to system size and improves the efficiency ...
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Based on the finite automata theory, a thinking of distributed deadlock supervisor is proposed to avoid deadlock in Knowledgeable Manufacturing systems, which is insensitive to system size and improves the efficiency of automata modeling and operating. The conception of the auto-correlation operation is presented, then the corresponding distributed deadlock supervisors are constructed, and thus the deadlock-free strategy of the knowledgeable manufacturing cell is obtained, which can be used to monitor status of the knowledge manufacturing cell in real-time and guarantees safe running of the system. Finally, a case study is presented to demonstrate the feasibility and effectiveness of the proposed strategy.
This paper presents a new rotor flux estimation algorithm using neural network for induction motor, based on the left-inversion method. Using the standard fifth-order model of the three-phase induction motor in a stat...
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This paper presents a new rotor flux estimation algorithm using neural network for induction motor, based on the left-inversion method. Using the standard fifth-order model of the three-phase induction motor in a stationary two axes reference frame, the flux ldquoassumed inherent sensorrdquo is constructed and its left-invertible is validated. The artificial neural network (ANN) left-inversion flux estimator is composed of two relatively independent parts - a static ANN used to approximate the complex nonlinear function and several differentiators used to represent its dynamic behaviors, so that the ANN left-inversion is a special kind of dynamic ANN in essence. The performance of the proposed algorithm is tested through simulation and experiment, proving good behavior in both transient and steady-state operating conditions.
In this paper, the finite-time tracking problem is investigated for a nonholonomic wheeled mobile robot in a fifth-order dynamic model. We consider the whole tracking error system as a cascaded system. Two continuous ...
In this paper, the finite-time tracking problem is investigated for a nonholonomic wheeled mobile robot in a fifth-order dynamic model. We consider the whole tracking error system as a cascaded system. Two continuous global finite-time stabilizing controllers are designed for a second-order subsystem and a third-order subsystem respectively. Then finite-time stability results for cascaded systems are employed to prove that the closed-loop system satisfies the finite-time stability. Thus the closed-loop system can track the reference trajectory in finite-time when the desired velocities satisfy some conditions. In particular, we discuss the control gains selection for the third-order finite-time controller and give sufficient conditions by using Lyapunov and backstepping techniques. Simulation results demonstrate the effectiveness of our method.
The ability to detect and follow a specific person is a key prerequisite of service mobile robots in indoor environments. A novel method for tracking and following a specific person with a mobile robot by combining vi...
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ISBN:
(纸本)9781424420575
The ability to detect and follow a specific person is a key prerequisite of service mobile robots in indoor environments. A novel method for tracking and following a specific person with a mobile robot by combining vision and laser range information is proposed. The vision module which integrates the color matching method using the Horizontal-Projecting Probability Histogram (HPPH) of upper body color clothes region with the Unscented Particle Filter (UPF) tracking method is developed and, at the same time, the laser module detects the pairs of legs to measure the distance from mobile robot. The information is integrated in a detection procedure that returns the direction and the distance of the target person. The proportional compensation method is utilized to enable the robot to follow the target person steadily. Experimental results validate the robust performance of the approach.
Previous studies mostly assume deterministic interactions among neighboring individuals for games on graphs. In this paper, we relax this assumption by introducing stochastic interactions into the spatial Prisoner’s ...
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Previous studies mostly assume deterministic interactions among neighboring individuals for games on graphs. In this paper, we relax this assumption by introducing stochastic interactions into the spatial Prisoner’s dilemma game, and study the effects of interaction stochasticity on the evolution of cooperation. Interestingly, simulation results show that there exists an optimal region of the intensity of interaction resulting in a maximum cooperation level. Moreover, we find good agreement between simulation results and theoretical predictions obtained from an extended pair-approximation method. We also show some typical snapshots of the system and investigate the mean payoffs for cooperators and defectors. Our results may provide some insight into understanding the emergence of cooperation in the real world where the interactions between individuals take place in an intermittent manner.
Multicommunity population systems may reach a consensus state where the fractions of each species in different communities agree on a common value. In this paper, by analyzing the evolutionary dynamics based on an ext...
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Multicommunity population systems may reach a consensus state where the fractions of each species in different communities agree on a common value. In this paper, by analyzing the evolutionary dynamics based on an extended replicator equation incorporating community effects, the consensus problem of population systems with n communities is studied. In particular, the simple case of two communities is investigated in detail. In general, for n communities, a sufficient and necessary condition for population systems to reach a consensus of coexistent state is provided. Regarding the population dynamics for the four different types of games, whether the population systems can achieve consensus is determined. The dynamics of community-structured populations shows richer features than nonstructured populations, and some nontrivial phenomena arising from different community-structured population systems are illustrated with concrete numerical examples.
A model-based matching method is proposed for welded joint localization and recognition. Simple parameterized joint models are defined, which approach the actual joint pose fast in a iterative style by using the parti...
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A model-based matching method is proposed for welded joint localization and recognition. Simple parameterized joint models are defined, which approach the actual joint pose fast in a iterative style by using the partial Hausdorff distance (PHD) as the similarity measurement. Statistical analysis is employed to determine the matching parameters adaptively, and the dimension of parameter space is decreased by performing the estimation on the structured light plane, which make a robust and real-time performance. Experiments show that accurate result can be acquired in real time, which meets the actual applications' requirements.
We consider the output feedback stabilizability of networked controlsystems with bounded packet loss. A packet-loss dependent Lyapunov function is adopted to design packet-loss dependent stabilizing output feedback c...
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We consider the output feedback stabilizability of networked controlsystems with bounded packet loss. A packet-loss dependent Lyapunov function is adopted to design packet-loss dependent stabilizing output feedback controllers by resolving some linear matrix inequalities. Moreover, two types of packet-loss processes are discussed: one is the arbitrary packet-loss process, and the other is the Markovian packet-loss process. A numerical example and some simulations are worked out to demonstrate the effectiveness of the proposed design technique.
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