A mineral is a natural, homogeneous solid with a definite chemical composition and a highly ordered atomic arrangement. Recently, fast and accurate mineral identification/classification became a necessity. Energy Disp...
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A mineral is a natural, homogeneous solid with a definite chemical composition and a highly ordered atomic arrangement. Recently, fast and accurate mineral identification/classification became a necessity. Energy Dispersive X-ray Spectrometers integrated with Scanning Electron Microscopes (SEM) are used to obtain rapid and reliable elemental analysis or chemical characterization of a solid. However, mineral identification is challenging since there is wide range of spectral dataset for natural minerals. The more mineralogical data acquired, time required for classification procedures increases. Moreover, applied instrumental conditions on a SEM-EDS differ for various applications, affecting the produced X-ray patterns even for the same mineral. This study aims to test whether C5.0 decisiontree is a rapid and reliable method algorithm for classification and identification of various natural magmatic minerals. Ten distinct mineral groups (olivine, Orthopyroxene, clinopyroxene, apatite, amphibole, plagioclase, K-feldspar, zircon, magnetite, biotite) from different igneous rocks have been analyzed on SEM-EDS. 4601 elemental X-ray intensity data have been collected under various instrumental conditions. 2400 elemental data have been used to train and the remaining 2201 data have been tested to identify the minerals. The vast majority of the test data have been classified accurately. Additionally, high accuracy has been reached on the minerals with similar chemical composition, such as olivine ((Mg,Fe)(2)[SiO4]) and orthopyroxene ((Mg,Fe)(2)[SiO6]). Furthermore, two members from amphibole group (magnesiohastingsite, tschermakite) and two from clinopyroxene group (diopside, hedenbergite) have been accurately identified by the decision tree algorithm. These results demonstrate that C5.0 decision tree algorithm is an efficient method for mineral group classification and the identification of mineral members. (C) 2015 Elsevier Ltd. All rights reserved.
The main focus of this study is to assess the slump characteristics of high-performance concrete (HPC) using decisiontree (DT) and support vector regression (SVR) models. In the first step, the models were solely fed...
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The main focus of this study is to assess the slump characteristics of high-performance concrete (HPC) using decisiontree (DT) and support vector regression (SVR) models. In the first step, the models were solely fed via HPC samples to reproduce the slump rates. By coupling phasor particle swarm optimization (PPSO) to main models, hybrid DT-PPSO and SVR-PPSO frameworks, simulate the slump rates accurately. Using the correlation of determination and root mean square error (MAE) metrics for the DT, 96.04 and 5.097 were computed, respectively. SVR was obtained at 92.62 and 6.965, alternatively. In the hybrid approach, DT-PPSO could improve by 3% and 55% in terms of correlation of determination and root MAE, respectively. DT-PPSO appeared high-accuracy model compared to others;however, a single DT had more desirable results than SVR. Overall, the advantages of this study encompass its methodological approach, comparative insights, and practical relevance, offering valuable contributions to the understanding and prediction of mechanical slump in HPC.
The endeavor of the present research is to nowcast the spatial visibility during fog over the airport of Kolkata (22.6 degrees N;88.4 degrees E), India, with artificial neural network (ANN) model. The identification o...
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The endeavor of the present research is to nowcast the spatial visibility during fog over the airport of Kolkata (22.6 degrees N;88.4 degrees E), India, with artificial neural network (ANN) model. The identification of dominant parameters influencing the visibility during wintertime (November-February) fog over the region is made using the decision tree algorithm. The decisiontree is constructed by computing the entropy of the parameters collected during the period from 2001 to 2011. The parameters having minimum entropy are selected as the most useful parameters because it has maximum certainty in influencing the visibility. The result reveals that the moderate range of NO2 (67-134 mu g/m(3)) is the most dominant parameter compared with other parameters that influence the visibility during wintertime fog over Kolkata and is selected as the first node of the tree. The decisiontree approach led to select five such parameters having minimum entropy for affecting maximum the visibility during fog over Kolkata airport. The selected parameters are NO2, wind speed, relative humidity, CO and temperature. ANN model is developed with the selected parameters as the input in the form of multilayer perceptron with back propagation learning technique for forecasting the 3 hourly visibility during wintertime fog over Kolkata airport. The result reveals that the forecast of visibility of different categories is possible with ANN model. However, the best forecast is obtained for very dense visibility within the 50 m horizontal distance. The result is validated with observation, and the forecast error is estimated.
Middle East Respiratory Syndrome, which is a respiratory disease caused by MERS coronavirus, is known to be an endemic disease spread in Kingdom of Saudi Arabia, or KSA. On May 20, 2015, it has massively occurred in R...
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ISBN:
(纸本)9788996865063
Middle East Respiratory Syndrome, which is a respiratory disease caused by MERS coronavirus, is known to be an endemic disease spread in Kingdom of Saudi Arabia, or KSA. On May 20, 2015, it has massively occurred in Republic of Korea, with 186 confirmed cases, 36 deaths. In this paper, we analyzed sonic features of MERS-CoV's transmission route by a new molecular approach. We have collected DNA sequences of MERS-CoV from 15 different regions in the world, including some regions of KSA. We have converted the DNA sequences into amino acid sequences and used Apriori and decision tree algorithm to found the similarities and differences between different MERS-CoVs' amino acid sequences. Then, we drew some conclusions about MERS's transmission routes by using these results.
This paper discusses the basic operating principle and the development status of data mining technology, analyzes the insufficiency of the existing psychological management system, and proposes the development trend o...
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This paper discusses the basic operating principle and the development status of data mining technology, analyzes the insufficiency of the existing psychological management system, and proposes the development trend of psychological health education in colleges. According to an analysis on factors affecting college students' mental health and the deviation between the reality and the current number of students with psychological abnormality, this paper studies the application of data mining technology and puts forward a system based on data mining that combines the classified data mining technology with the existing psychological management system.
As the core link and an important content, credit risk assessment plays vital special role for moderate operation of commercial banks. It is important to work out credit risk assessment model of commercial banks. A sy...
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ISBN:
(纸本)9781467371438
As the core link and an important content, credit risk assessment plays vital special role for moderate operation of commercial banks. It is important to work out credit risk assessment model of commercial banks. A system of credit risk assessment which contains five aspects including 25 indicators is proposed. Based on establishment of credit risk assessment model, empirical analysis is carried out. The result shows this model has high accuracy of predication, better reliability and strong assessment ability.
Analysis of factors influencing the severity of occupational accidents in manufacturing systems is of vital importance for sustainable manufacturing in a business environment. The aim of this study is to identify occu...
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Analysis of factors influencing the severity of occupational accidents in manufacturing systems is of vital importance for sustainable manufacturing in a business environment. The aim of this study is to identify occupational health and safety risks in the Turkish textile manufacturing industry, which includes "manufacturing of textiles," "manufacturing of wearing apparel," and "manufacturing of leather and related products". There is no study in the literature that examines the risks related to occupational health and safety in Turkish textile manufacturing based on occupational accident records from 2013 to 2019. To fill this gap in the literature, data-driven modeling is conducted to analyze 139,092 accident records including enterprise information, accident information, injured person information, and accident outcome information, which are obtained from the Ministry of Family, Labor, and Social Services in Turkiye. The result of this study showed that there are 50 injury accident decision rules based on 15 distinct accident predictors, which will support decisions for the efficient use of limited resources, the development of effective accident prevention policies, and the stability of the sector.
Assessment of the spatial distribution of potential pathways of sediment transport and the degree of linkage between sediment sources and the channel network within a watershed represents a valuable analysis for infor...
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Assessment of the spatial distribution of potential pathways of sediment transport and the degree of linkage between sediment sources and the channel network within a watershed represents a valuable analysis for informing management decisions on sediment yield and transfer. Given the limitations of conventional methods for determining index of sediment connectivity (IC), there is a need to provide a flexible and efficient approach with the ability to apply different factors. In this regard, five decisiontree-based machine learning models: M5 prime (M5P), random tree (RT), random forest (RF), alternating model tree (AMT), and reduced error pruning tree (REPT) were tested using geomorphic and climatic factors. Two databases were constructed with 200 and 1600 classes at 50 watersheds in Queensland, Australia. In these models, IC was assessed as an output parameter and six attributes that affect IC were assigned as input parameters (i.e., elevation, slope, area, length of stream channel, normalized difference vegetation index, and rainfall). Statistical validation and comparison of model predictions with calculated IC values based on the approach of Borselli et al. (Catena 75:268-277, 2008) were performed. Based on the statistical criteria, the RF model produced the most robust estimations of IC compared to other models and performed very well for IC modelling, especially in smaller subsections of watersheds. Accordingly, these findings can play an effective role for implementing watershed management and soil and water resources management measures.
This paper has conducted a study on the applications of track and field equipment training based on ID3 algorithm of decisiontree model. For the selection of the elements used by decisiontree, this paper can be divi...
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This paper has conducted a study on the applications of track and field equipment training based on ID3 algorithm of decisiontree model. For the selection of the elements used by decisiontree, this paper can be divided into track training equipment, field events training equipment and auxiliary training equipment according to the properties of track and field equipment. The decisiontree that regards track training equipment as root nodes has been obtained under the conditions of lowering computation cost through the selection of data as well as the application and optimization of ID3 algorithm model.
Under the modern education system of China, the annual scholarship evaluation is a vital thing for many of the collegestudents. This paper adopts the classification algorithm of decisiontree C4.5 based on the betteri...
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Under the modern education system of China, the annual scholarship evaluation is a vital thing for many of the collegestudents. This paper adopts the classification algorithm of decisiontree C4.5 based on the bettering of ID3 algorithm and constructa data set of the scholarship evaluation system through the analysis of the related attributes in scholarship evaluation *** also having found some factors that plays a significant role in the growing up of the college students through analysis and re-search of moral education, intellectural education and culture&PE.
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