The present work aimed to evaluate and optimize the design of an artificial neural network (ANN) combined with an optimization algorithm of genetic algorithm (GA) for the calculation of slope stability safety factors (SF) in a pure cohesive slope. To make datasets of training and testing for the developed predictive models, 630 finite element limit equilibrium (FELE) analyses were performed. Similar to many artificial intelligence-based solutions, the database was involved in 189 testing datasets (e.g., 30% of the entire database) and 441 training datasets; for example, a range of 70% of the total database. Moreover, variables of multilayer perceptron (MLP) algorithm (for example, number of nodes in any hidden layer) and the algorithm of GA like population size was optimized by utilizing a series of trial and error process. The parameters in input, which were used in the analysis, consist of slope angle (β), setback distance ratio (b/B), applied stresses on the slope (Fy) and undrained shear strength of the cohesive soil (Cu) where the output was taken SF. The obtained network outputs for both datasets from MLP and GA-MLP models are evaluated according to many statistical indices. A total of 72 MLP trial and error (e.g., parameter study) the optimal architecture of 4 × 8 × 1 were determined for the MLP structure. Both proposed techniques result in a proper performance; however, according to the statistical indices, the GA–MLP model can somewhat accomplish the least mean square error (MSE) when compared to MLP. In an optimized GA–MLP network, coefficient of determination (R2) and root mean square error (RMSE) values of (0.975, and 0.097) and (0.969, and 0.107) were found, respectively, to both of the normalized training and testing datasets.
Applied Intelligence - Pharmaceutical drug combinations can effectively treat various medical conditions. However, some combinations can cause serious adverse drug reactions (ADR). Therefore,... 相似文献
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Despite a large body of work on XPath query processing in relational environment, systematic study of queries containing not-predicates have received little attention in the literature. Particularly, several xml supports of industrial-strength commercial rdbms fail to efficiently evaluate such queries. In this paper, we present an efficient and novel strategy to evaluate not-twig queries in a tree-unaware relational environment. not-twig queries are XPath queries with ancestor–descendant and parent–child axis and contain one or more not-predicates. We propose a novel Dewey-based encoding scheme called Andes (ANcestor Dewey-based Encoding Scheme), which enables us to efficiently filter out elements satisfying a not-predicate by comparing their ancestor group identifiers. In this approach, a set of elements under the same common ancestor at a specific level in the xml tree is assigned same ancestor group identifier. Based on this scheme, we propose a novel sql translation algorithm for not-twig query evaluation. Experiments carried out confirm that our proposed approach built on top of an off-the-shelf commercial rdbms significantly outperforms state-of-the-art relational and native approaches. We also explore the query plans selected by a commercial relational optimizer to evaluate our translated queries in different input cardinality. Such exploration further validates the performance benefits of Andes. 相似文献
The analysis method of optimal tracking performance is proposed for multiple‐input multiple‐output (MIMO) linear time‐invariant (LTI) systems under disturbance rejection. An H2 criterion of the error signal between the output of the plant and the reference signal is used as a measure for the tracking performance. Spectral factorization is applied to obtain the optimal solution of the system tracking error. The explicit expressions are derived for this minimal tracking error with respect to random reference signals under disturbance rejection. It is shown that the nonminimum phase zeros, the zero direction, the unstable poles, the pole direction of a given plant, statistical characteristics of the reference input signal, and disturbance signal have a negative effect on a feedback system's ability to reduce the system error with disturbance rejection. The results show that the optimal tracking performance will further be damaged because of disturbance rejection. Some typical examples are given to illustrate the theoretical results. 相似文献
In this paper, we propose a vertical and floor line-based monocular simultaneous localization and mapping (SLAM) system which utilizes vertical lines, floor lines, and vanishing points as sensory input to perform robust SLAM in corridor environments. By combining three map feature types, our design can help a robot to perform accurate pose estimation, repeatable loop closure, and to construct a more expressive environmental map. As a primitive element of a geometric structure, a line segment has one additional dimension compared to a point feature, thereby allowing the use of line segments to easily represent a geometric structure using a smaller number of features. This system presents map features on a 2D ground space: the vertical line as a projection point, the floor line as the original line, and the vanishing point as a directional vector. Although the vertical line, floor line, and vanishing point use different parameterization and initialization methods, their measurement models are integrated into a unified extended Kalman filter (EKF) framework. Experimental results show that our system can be deployed in a structured indoor environment as a suitable SLAM solution. 相似文献