Lithology identification serves as a crucial foundation for the precise exploration and safe exploitation of geological resources. However, challenges arise from the inherent imbalance and overlap present in logging d...
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Lithology identification serves as a crucial foundation for the precise exploration and safe exploitation of geological resources. However, challenges arise from the inherent imbalance and overlap present in logging data, making the accurate identification of lithology a complex task. Addressing these challenges effectively, this paper introduces a novel algorithm,the Error Correcting Output Code algorithm based on Hierarchical Clustering(HC-ECOC). The proposed algorithm initially formulates a coding matrix using distance and overlap measures between class clusters. Subsequently, it extends the length of the coding matrix by considering both the accuracy of the integrated classifier and the diversity among base classifiers. To evaluate the efficacy of the proposed method, comparisons were conducted with alternative algorithms using UCI datasets and an authentic lithology dataset. The results unequivocally demonstrate the superior performance of our algorithm.
This study extracted the main factors from a questionnaire,measurement results,and the analysis of sEMG signals to establish a method of evaluating muscle *** measured factors(rating of perceived exertion,heart rate,m...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
This study extracted the main factors from a questionnaire,measurement results,and the analysis of sEMG signals to establish a method of evaluating muscle *** measured factors(rating of perceived exertion,heart rate,mileage) and five factors obtained from the analysis of sEMG signals(root mean square,mean absolute value,variance,times of zero crossing,median frequency) were *** the F-test,the correlation analysis,and the principal component analysis,we finally extracted six factors as the main factors that have a big influence on muscle fatigue.
With the development of artificial intelligence, the anomaly detection plays more and more important role in security monitoring field. Because it is difficult to label abnormal data, most of the supervised methods co...
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This paper focuses on the problem of stability analysis for Takagi-Sugeno systems with time-varying delays. Firstly,a suitable Lyapunov-Krasovskii functional(LKF) containing fuzzy line-integral Lyapunov functional is ...
This paper focuses on the problem of stability analysis for Takagi-Sugeno systems with time-varying delays. Firstly,a suitable Lyapunov-Krasovskii functional(LKF) containing fuzzy line-integral Lyapunov functional is constructed, which can introduce membership functions information while avoiding emerging the time-derivatives of membership functions. Then, a generalized free-matrix-based integral inequality is applied to estimate the derivative of the LKF. As a result, a less conservative stability criterion is obtained. Finally, a numerical example is carried out to illustrate the effectiveness and merits of our method.
This paper concerns with the exponential stability of delayed neural networks via Lyapunov-Krasovskii functional(LKF) method. Initially, an improved augmented delay-product-type LKF containing an additional double int...
This paper concerns with the exponential stability of delayed neural networks via Lyapunov-Krasovskii functional(LKF) method. Initially, an improved augmented delay-product-type LKF containing an additional double integral state is established, which introduces more delayed states and has less conservatism. In the LKF's derivative, the function has high order of delay due to the existence of exponent. Thus, in order to obtain tractable linear matrix inequalities, three state vectors are used to reduce the order of the function to cubic. Secondly, to achieve the negative-definiteness requirement, a negative-determination lemma for cubic functions with less conservatism is employed. Then, a less conservative delay-dependent stability criterion for neural networks with time-varying delays is established. Finally, the validity of the proposed delay-dependent stability criterion is illustrated by two numerical examples.
This paper is concerned with H performance state estimation of static neural networks with a time-varying ***, a PI estimator with exponential term is used to estimate neuron states based on output measurement. Second...
This paper is concerned with H performance state estimation of static neural networks with a time-varying ***, a PI estimator with exponential term is used to estimate neuron states based on output measurement. Second, an augmented Lyapunov-Krasovskii functional（LKF） containing delay-product-type non-integral terms and single integral terms is constructed by introducing negative definite terms. After that, a criterion with less conservatism is derived based on extended reciprocally convex matrix inequality. Finally, a numerical example is provided to reveal the effectiveness of the proposed approach.
This paper investigates the delay-dependent stability of time-delayed load frequency control(LFC) systems with multiple energy structures based on Lyapunov theory and linear matrix inequality(LMI) ***,a multi-area del...
This paper investigates the delay-dependent stability of time-delayed load frequency control(LFC) systems with multiple energy structures based on Lyapunov theory and linear matrix inequality(LMI) ***,a multi-area delayed LFC model considering multiple renewable energy structures is ***,in order to improve the computation efficiency of stability analysis of large scale LFC systems,a new reconstruction technique for system model is ***,the improved delay-dependent stability criteria are established based on reconstructed model by using the Lyapunov stability ***,case studies are based on two-area LFC *** with the criterion based on the original model without reconstruction,the calculation efficiency of proposed stability criteria has been greatly improved with the cost of small accuracy,and the calculation accuracy is better than the previous methods.
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