This paper presents a weak convergence residual algorithm for finding a fixed point of a nonexpansive mapping in a real Hilbert space. To study the numerical behavior of the algorithm it is included an extensive serie...
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This paper presents a weak convergence residual algorithm for finding a fixed point of a nonexpansive mapping in a real Hilbert space. To study the numerical behavior of the algorithm it is included an extensive series of numerical experiments. Our computational experiments show that the new algorithm is computationally efficient.
In this paper a family of methods for multi-body dynamic simulation is introduced. Equations of motion are obtained using a set of Cartesian coordinates and projected onto a set of independent relative coordinates usi...
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In this paper a family of methods for multi-body dynamic simulation is introduced. Equations of motion are obtained using a set of Cartesian coordinates and projected onto a set of independent relative coordinates using the concept of velocity transformation. Open-chain systems are solved directly following either a fully recursive or a semi-recursive procedure. Closed-chain systems are solved in two steps;kinematic loops are opened by removing either some kinematic joints or a rigid body, and the resulting open-chain system is solved;closure-of-the-loop conditions are imposed by means of a second velocity transformation. The dynamic formalisms have been developed so as to handle both non-stiff and stiff systems. Non-stiff systems are solved by means of an Adams-Bashforth-Moulton numerical integration scheme, which requires the computation of the function derivatives. Stiff problems are integrated by using either BDF or NDF methods, which require the computation of the residual of the equations of motion and, optionally, the evaluation of the Jacobian matrix. The proposed algorithms have been implemented using an Object-Oriented Programming approach that makes it possible to re-use the source code, keeping programs smaller, cleaner and easier to maintain. Practical examples that illustrate the performance of these implementations are included. These examples have also been solved using a commercial multi-body simulation package and comparative results are included. In most cases, the algorithms here presented outperform those implemented in the commercial package, leading to important savings in terms of total computation times.
The paper describes the extension of the composite rigid body formalism for the flexible multibody systems. The extension has been done in such a way that all advantages of the formalism with respect to the coordinate...
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The paper describes the extension of the composite rigid body formalism for the flexible multibody systems. The extension has been done in such a way that all advantages of the formalism with respect to the coordinates of large motion of rigid bodies are extended to the flexible degrees of freedom, e.g. the same recursive treatment of both coordinates and no appearance of O(n(3)) computational complexity terms due to the flexibility. This extension has been derived for both open loop and closed loop systems of flexible bodies. The comparison of the computational complexity of this formalism with other known approaches has shown that the described formalism of composite rigid body and the residual algorithm based on it are more efficient formalisms for small number of bodies in the chains and deformation modes than the usual recursive formalism of articulated body inertia.
A new formulation of the partial element equivalent circuit (PEEC) method is presented, which is well suited to be combined with compression and matrix-vector product acceleration techniques. In particular, taking adv...
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A new formulation of the partial element equivalent circuit (PEEC) method is presented, which is well suited to be combined with compression and matrix-vector product acceleration techniques. In particular, taking advantage of the rank-deficiency of the magnetic and electric field couplings, the adaptive cross approximation (ACA) technique is firstly, adopted to compress PEEC interaction matrices, namely partial inductances and coefficients of potential matrices. Differently from the use of ACA in conjunction with the method of moments, in this study, magnetic and electric field couplings are kept distinct, thus allowing to efficiently compress both magnetic and electric field interaction matrices. Secondly, the compressed matrices are used to accelerate the transient analysis of PEEC circuits. Indeed, Kirchoff voltage and current laws are enforced to PEEC circuits so that matrix-vector products involving the interaction matrices can be significantly accelerated in virtue of their compression, thus leading to very good speed-ups when using iterative solvers like the generalised method of residuals algorithm. Numerical results demonstrate the validity, accuracy and performance of the proposed approach in terms of both memory usage saving and transient analysis speed-up.
Abnormal driving behavior is one of the main causes of roadway collisions. In most studies of abnormal driving behavior, the abnormal driving status is detected and analyzed using classification algorithms directly or...
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Abnormal driving behavior is one of the main causes of roadway collisions. In most studies of abnormal driving behavior, the abnormal driving status is detected and analyzed using classification algorithms directly or using unsupervised learning algorithms to classify reconstruction or prediction residuals. However, abnormal driving behavior data are difficult to acquire and label. Also, a class imbalance issue is inherent in the algorithm training process due to the relatively sparse data for abnormal driving behavior. Moreover, current studies that include residual analysis tend to focus on individual points and thus fail to capture the continuity characteristic of abnormal driving *** address these problems, a long short-term memory-residual (LSTM-R) algorithm is proposed to detect abnormal driving behavior in real time. The proposed algorithm (referred to simply as LSTM-R) has two steps. First, an LSTM network is used to fit the current vehicle kinematic data based on historical data to obtain the root mean square residual at each moment. Second, a time window -based residual algorithm is designed and employed to detect abnormal driving behavior accord-ing to the magnitude and continuity of the residuals. To verify the effectiveness of LSTM-R, an experimental test was conducted in Nanjing, China. The vehicle kinematic data were collected non -intrusively using a *** addition, AdaCost, SMOTEBoost, EasyEnsemble, LightGBM-residual, and linear regression -residual algorithms were employed for comparison with the proposed algorithm to assess its effectiveness. The effects of (1) the degree-of-fit of the LSTM network, (2) the LSTM-R parameters, and (3) the abnormal driving behavior percentage on the detection results were analyzed in detail. First, both the underfitting and overfitting of the LSTM network compromise the detection per-formance. Second, within a certain range of values, the LSTM-R parameters have little effect on the detection results.
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