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1.
The aim of the research is evaluating the classification performances of eight different machine-learning methods on the antepartum cardiotocography (CTG) data. The classification is necessary to predict newborn health, especially for the critical cases. Cardiotocography is used for assisting the obstetricians’ to obtain detailed information during the pregnancy as a technique of measuring fetal well-being, essentially in pregnant women having potential complications. The obstetricians describe CTG shortly as a continuous electronic record of the baby's heart rate took from the mother's abdomen. The acquired information is necessary to visualize unhealthiness of the embryo and gives an opportunity for early intervention prior to happening a permanent impairment to the embryo. The aim of the machine learning methods is by using attributes of data obtained from the uterine contraction (UC) and fetal heart rate (FHR) signals to classify as pathological or normal. The dataset contains 1831 instances with 21 attributes, examined by applying the methods. In the paper, the highest accuracy displayed as 99.2%. 相似文献
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For many-objective optimization problems, how to get a set of solutions with good convergence and diversity is a difficult and challenging work. In this paper, a new decomposition based evolutionary algorithm with uniform designs is proposed to achieve the goal. The proposed algorithm adopts the uniform design method to set the weight vectors which are uniformly distributed over the design space, and the size of the weight vectors neither increases nonlinearly with the number of objectives nor considers a formulaic setting. A crossover operator based on the uniform design method is constructed to enhance the search capacity of the proposed algorithm. Moreover, in order to improve the convergence performance of the algorithm, a sub-population strategy is used to optimize each sub-problem. Comparing with some efficient state-of-the-art algorithms, e.g., NSGAII-CE, MOEA/D and HypE, on six benchmark functions, the proposed algorithm is able to find a set of solutions with better diversity and convergence. 相似文献
5.
The principles and design of “active” self‐propelling particles that can convert energy, move directionally on their own, and perform a certain function is an emerging multidisciplinary research field, with high potential for future technologies. A simple and effective technique is presented for on‐demand steering of self‐propelling microdiodes that move electroosmotically on water surface, while supplied with energy by an external alternating (AC) field. It is demonstrated how one can control remotely the direction of diode locomotion by electronically modifying the applied AC signal. The swimming diodes change their direction of motion when a wave asymmetry (equivalent to a DC offset) is introduced into the signal. The data analysis shows that the ability to control and reverse the direction of motion is a result of the electrostatic torque between the asymmetrically polarized diodes and the ionic charges redistributed in the vessel. This novel principle of electrical signal‐coded steering of active functional devices, such as diodes and microcircuits, can find applications in motile sensors, MEMs, and microrobotics. 相似文献
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The ensemble learning paradigm has proved to be relevant to solving most challenging industrial problems. Despite its successful application especially in the Bioinformatics, the petroleum industry has not benefited enough from the promises of this machine learning technology. The petroleum industry, with its persistent quest for high-performance predictive models, is in great need of this new learning methodology. A marginal improvement in the prediction indices of petroleum reservoir properties could have huge positive impact on the success of exploration, drilling and the overall reservoir management portfolio. Support vector machines (SVM) is one of the promising machine learning tools that have performed excellently well in most prediction problems. However, its performance is a function of the prudent choice of its tuning parameters most especially the regularization parameter, C. Reports have shown that this parameter has significant impact on the performance of SVM. Understandably, no specific value has been recommended for it. This paper proposes a stacked generalization ensemble model of SVM that incorporates different expert opinions on the optimal values of this parameter in the prediction of porosity and permeability of petroleum reservoirs using datasets from diverse geological formations. The performance of the proposed SVM ensemble was compared to that of conventional SVM technique, another SVM implemented with the bagging method, and Random Forest technique. The results showed that the proposed ensemble model, in most cases, outperformed the others with the highest correlation coefficient, and the lowest mean and absolute errors. The study indicated that there is a great potential for ensemble learning in petroleum reservoir characterization to improve the accuracy of reservoir properties predictions for more successful explorations and increased production of petroleum resources. The results also confirmed that ensemble models perform better than the conventional SVM implementation. 相似文献
7.
A new matching cost computation method based on nonsubsampled contourlet transform (NSCT) for stereo image matching is proposed in this paper. Firstly, stereo image is decomposed into high frequency sub-band images at different scales and along different directions by NSCT. Secondly, by utilizing coefficients in high frequency domain and grayscales in RGB color space, the computation model of weighted matching cost between two pixels is designed based on the gestalt laws. Lastly, two types of experiments are carried out with standard stereopairs in the Middlebury benchmark. One of the experiments is to confirm optimum values of NSCT scale and direction parameters, and the other is to compare proposed matching cost with nine known matching costs. Experimental results show that the optimum values of scale and direction parameters are respectively 2 and 3, and the matching accuracy of the proposed matching cost is twice higher than that of traditional NCC cost. 相似文献
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如今我国信息化技术全面发展,尤其对于工程测量工作领域来讲,不管是在工程建设和管理方面都产生不小的支撑引导效用。由此,笔者具体结合如今工程建设信息化测绘核心任何以及设备布置细节,进行结构整体安全管理周期和周边地理空间信息技术发展能效整理解析,试图将工程测量最新发展机遇和技术挑战问题处理完全。希望能够借此为日后一定时期范围内相关工程测量规划主体提供合理指导性建议内容,最终为我国各类工程事业可持续发展前景绽放奠定深刻适应基础。 相似文献
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为了提高注入剖面测井的准确性,研制了一种新型注入剖面组合测井仪。该仪器由流量处理单元、伽马处理单元、井温处理单元、磁性定位处理单元、调制式传输、电源电路六部分组成。一次下井可同时测取流量、伽马、井温、磁性定位四组参数。具有测取资料精度高、单芯电缆传输、流量可单点测量也可连续测量以厦现场监测和维修方便等特点。 相似文献
10.
It is shown that, for the spectrum analysis of digital quasi-periodic signals, one must use a procedure based on approximating the sequence of data readouts by a first-order trigonometric polynomial with a varying frequency of its harmonic functions. 相似文献