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981.
Protein-protein interactions play a crucial role in the cellular process such as metabolic pathways and immunological recognition. This paper presents a new domain score-based support vector machine (SVM) to infer protein interactions, which can be used not only to explore all possible domain interactions by the kernel method, but also to reflect the evolutionary conservation of domains in proteins by using the domain scores of proteins. The experimental result on the Saccharomyces cerevisiae dataset demonstrates that this approach can predict protein-protein interactions with higher performances compared to the existing approaches. 相似文献
982.
Current deep-learning models are mostly built upon neural networks, i.e. multiple layers of parameterized differentiable non-linear modules that can be trained by backpropagation. In this paper, we explore the possibility of building deep models based on non-differentiable modules such as decision trees. After a discussion about the mystery behind deep neural networks, particularly by contrasting them with shallow neural networks and traditional machine-learning techniques such as decision trees and boosting machines, we conjecture that the success of deep neural networks owes much to three characteristics, i.e. layer-by-layer processing, in-model feature transformation and sufficient model complexity. On one hand, our conjecture may offer inspiration for theoretical understanding of deep learning; on the other hand, to verify the conjecture, we propose an approach that generates deep forest holding these characteristics. This is a decision-tree ensemble approach, with fewer hyper-parameters than deep neural networks, and its model complexity can be automatically determined in a data-dependent way. Experiments show that its performance is quite robust to hyper-parameter settings, such that in most cases, even across different data from different domains, it is able to achieve excellent performance by using the same default setting. This study opens the door to deep learning based on non-differentiable modules without gradient-based adjustment, and exhibits the possibility of constructing deep models without backpropagation. 相似文献
983.
张宁 《福建工程学院学报》2017,(4):367-370
提出将一种进化的神经网络模型——极限学习机应用于短期电力负荷时间序列预测中,该方法具有模型参数设置少、训练速度快和良好的泛化能力等明显优点。通过实例分析表明该模型的预测精度要优于BP神经网络模型,同时也验证了该模型应用于短期负荷预测的有效性和可行性。 相似文献
984.
The validated Predicting Abusive Head Trauma (PredAHT) tool estimates the probability of abusive head trauma (AHT) based on combinations of six clinical features: head/neck bruising; apnea; seizures; rib/long-bone fractures; retinal hemorrhages. We aimed to determine the acceptability of PredAHT to child protection professionals. We conducted qualitative semi-structured interviews with 56 participants: clinicians (25), child protection social workers (10), legal practitioners (9, including 4 judges), police officers (8), and pathologists (4), purposively sampled across southwest United Kingdom. Interviews were recorded, transcribed and imported into NVivo for thematic analysis (38% double-coded). We explored participants’ evaluations of PredAHT, their opinions about the optimal way to present the calculated probabilities, and their interpretation of probabilities in the context of suspected AHT. Clinicians, child protection social workers and police thought PredAHT would be beneficial as an objective adjunct to their professional judgment, to give them greater confidence in their decisions. Lawyers and pathologists appreciated its value for prompting multidisciplinary investigations, but were uncertain of its usefulness in court. Perceived disadvantages included: possible over-reliance and false reassurance from a low score. Interpretations regarding which percentages equate to ‘low’, ‘medium’ or ‘high’ likelihood of AHT varied; participants preferred a precise % probability over these general terms. Participants would use PredAHT with provisos: if they received multi-agency training to define accepted risk thresholds for consistent interpretation; with knowledge of its development; if it was accepted by colleagues. PredAHT may therefore increase professionals’ confidence in their decision-making when investigating suspected AHT, but may be of less value in court. 相似文献
985.
986.
本文通过研究和分析数控冲加工的工艺特点,提出了在冲孔机的程序设计中应当注意的一些事项,将数控冲程序设计在生产过程应用中常见的问题进行剖析,并以相应的实例阐述了完成各项工作和解决具体问题的办法。 相似文献
987.
988.
阐述数据挖掘的分类及目的,总结分类器的构造方法,讲述分类中决策树的构建和修剪. 相似文献
989.
Applying stiffness migration method, a 3D finite element mechanical model is established to simulate the excavation and advance processes. By using 3D nonlinear finite element method, the tunnel boring machine (TBM) excavation process is dynamically simulated to analyze the stress and strain field status of surrounding rock and segment. The maximum tensile stress of segment ring caused by tunnel construction mainly lies in arch bottom and presents zonal distribution. The stress increases slightly and limitedly in the course of excavation. The maxi-mum and minimum displacements of segment, manifesting as zonal distribution, distribute in arch bottom and vault respectively. The displacements slightly increase with the advance of TBM and gradually tend to stability. 相似文献
990.
This paper presents an effective method for motion classification using the surface electromyographic (sEMG) signal collected
from the forearm. Given the nonlinear and time-varying nature of EMG signal, the wavelet packet transform (WPT) is introduced
to extract time-frequency joint information. Then the multi-class classifier based on the least squares support vector machine
(LS-SVM) is constructed and verified in the various motion classification tasks. The results of contrastive experiments show
that different motions can be identified with high accuracy by the presented method. Furthermore, compared with other classifiers
with different features, the performance indicates the potential of the SVM techniques combined with WPT in motion classification. 相似文献