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Updated Lithological Map in the Forest Zone of the Centre, South and East Regions of Cameroon Using Multilayer Perceptron Neural Network and Landsat Images

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Journal of Geoscience and Environment Protection 2021年第6期9卷 120-134页

作者： Charlie Gael Atangana Otele Mathias Akong Onabid Patrick Stephane Assembe Marcellin Nkenlifack URIFIA Department of Mathematics and Computer Science Faculty of Science University of Dschang Dschang Cameroon Department of Computer Science Higher Teacher Training College The University of Bamenda Bambili Cameroon Department of Computer Science Higher Technical Teacher Training College The University of Bamenda Bambili Cameroon Postgraduate School of Science Technology and Geoscience Geophysics and Geo-Exploration Unit University of Yaoundé-I Yaoundé Cameroon

The Multilayer Perceptron Neural Network (MLPNN) induction technique has been successfully applied to a variety of machine learning tasks, including the extraction and classification of image features. However, not much has been done in the application of MLPNN on images obtained by remote sensing. In this article, two automatic classification systems used in image feature extraction and classification from remote sensing data are presented. The first is a combination of two models: a MLPNN induction technique, integrated under ENVI (Environment for Visualizing Images) platform for classification, and a pre-processing model including dark subtraction for the calibration of the image, the principal components analysis (PCA) for band selections and Independent components analysis (ICA) as blind source separator for feature extraction of the Landsat image. The second classification system is a MLPNN induction technique based on the Keras platform. In this case, there was no need for pre-processing model. Experimental results show the two classification systems to outperform other typical feature extraction and classification methods in terms of accuracy for some lithological classes including Granite1 class with the highest class accuracies of 96.69% and 92.69% for the first and second classification system respectively. Meanwhile, the two classification systems perform almost equally with the overall accuracies of 53.01% and 49.98% for the first and second models respectively though the keras model has the advantage of not integrating the pre-processing model, hence increasing its efficiency. The application of these two systems to the study area resulted in the generation of an updated geological mapping with six lithological classes detected including the Gneiss, the Micaschist, the Schist and three versions of Granites (Granite1, Granite2 and Granite3).

关键词： Neural Network Multilayer Perceptron principal components analysis Independent components analysis Lithological Classification Geological Mapping

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Hydrogeochemical Assessment of Groundwater in the Precambrian Rocks, South Eastern Desert, Egypt

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Journal of Water Resource and Protection 2016年第3期8卷 293-310页

作者： Ashraf Embaby Moumtaz Razack Mathieu Lecoz Gilles Porel Department of Hydrogeology University of Poitiers Poitiers France Geology Department Faculty of Science Sohag University Sohag Egypt

This work refers to the characterization of the hydrochemistry of the southern part of the Eastern Desert in Egypt, on the basis of physico-chemical properties of groundwater occurring in the fractured Precambrian rocks inland and in sedimentary formations on the coastline of the Red Sea. Thirty-five groundwater samples have been collected from the study area for hydrochemical investigations to understand the sources of dissolved ions and assess the chemical quality of the groundwater. Several methods were used to interpret the hydrochemical data, i.e. graphical methods, principal components analysis, ions exchanges indices and saturation indices of various minerals. The results show that the major ionic relationships are Na+ > Ca2+ > Mg2+ and Cl- > > HCO3- and that groundwater chemical characteristics are controlled by natural geochemical processes but also, to a lesser extent, by anthropogenic activities. Natural minerals dissolution, ion exchanges and evaporation play a prominent role in the ion enrichment of groundwater. A comparison of groundwater quality in relation to WHO water quality standards proved that most of the water samples are not totally suitable for drinking water purpose.

关键词： Eastern Desert Pre-Cambrian Rocks Groundwater Hydrochemistry principal components analysis Egypt

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Research on Application of Enhanced Neural Networks in Software Risk analysis

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南昌工程学院学报 2006年第2期25卷 112-116,121页

作者： Zhenbang Rong Juhua Chen Mei Liu Yong Hu Sun Yat-sen University Guangzhou 510275 China University of Kansas 66045U. S.A

This paper puts forward a risk analysis model for software projects using enranced neural *** data for analysis are acquired through questionnaires from real software projects. To solve the multicollinearity in software risks, the method of principal components analysis is adopted in the model to enhance network *** solve uncertainty of the neural networks structure and the uncertainty of the initial weights, genetic algorithms is *** experimental result reveals that the precision of software risk analysis can be improved by using the erhanced neural networks model.

关键词： software risk analysis principal components analysis back propagation neural networks genetic algorithms

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Design and Implementation of Iris Pattern Recognition Using Wireless Network System

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Journal of Computer and Communications 2016年第7期4卷 15-21页

作者： Ali Abdulhafidh Ibrahim Thura Ali Khalaf Bashar Mudhafar Ahmed College of Science Al-Nahrain University Baghdad Iraq College of Information Engineering Al-Nahrain University Baghdad Iraq College of Engineering Al-Nahrain University Baghdad Iraq

The goal of this paper is to propose a fast and accurate iris pattern recognition system by using wireless network system. This paper consists of three parts: the first part includes two methods of the iris pattern recognition system: Libor Masek and genetic algorithms, the second part includes the compression-decompression process of iris image using principal Component analysis (PCA) as a data reduction method, in order to reduce image size, and the third part talks about wireless network. In this work, an iris image is transferred across wireless network which contains two independent-parallel lines connected to the central Personal Computer (PC) in order to be recognized at the end of each line, then the results of recognition are sent back to the central PC. The proposed genetic algorithm, which is used in this paper is more accurate than Masek algorithm and has low computational time and complexity, which makes this method better than Masek method in recognizing iris patterns.

关键词： Iris Recognition Genetic Algorithm principal components analysis Wireless Network

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Analyzing inspection results of Port State Control by using PCA

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International Journal of Technology Management 2014年第7期 67-70页

作者： Zhang Lian-feng Gang Long-hui Liu Zheng-jiang Navigation College of Dalian Maritime University Dalian 116026 China E-mail: z-tics@ *** Corresponding author Navigation College of Dalian Maritime University Dalian 116026 China E-mail:gloriagang@*** Dalian Maritime University Dalian 116026 China

The paper applied principal components analysis Method to analyze the PSC inspection results in the area of T-MOU and P-MOU. Set up the assessment of ship detention, the ships＇ main deficiencies of detentions were found out by the standardization of data processing and correlation matrix calculating. Provide the basis for shipping company to master the safety management focus and pass the PSC inspection.

关键词： Port State Control Detention Deficiencies principal components analysis

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Visualization of Multivariate Metabolomic Data

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Chinese Herbal Medicines 2011年第4期3卷 285-289页

作者： AA Ji-ye Laboratory of Metabolomics Key Laboratory of Drug Metabolism and PharmacokineticsChina Pharmaceutical University

Objective Although principal components analysis profiles greatly facilitate the visualization and interpretation of the multivariate data,the quantitative concepts in both scores plot and loading plot are rather *** article introduced three profiles that assisted the better understanding of metabolomic *** The discriminatory profile,heat map, and statistic profile were developed to visualize the multivariate data obtained from high-throughput GC-TOF-MS analysis. Results The discriminatory profile and heat map obviously showed the discriminatory metabolites between the two groups,while the statistic profile showed the potential markers of statistic *** The three types of profiles greatly facilitate our understanding of the metabolomic data and the identification of the potential markers.

关键词： discriminatory profile heat map metabolomic data principal components analysis statistic profile

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Study on GC-MS fingerprint of petroleum ether fraction of Shenqi Jiangtang Granules

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Digital Chinese Medicine 2021年第1期4卷 32-41页

作者： LI Bingbing WANG Qian LI Caixia HUANG Wenjing CHEN Guoliang GUAN Yongxia Muhammad Ishaq XIAO Xue YAN Shikai State Key Laboratory of Generic Manufacture Technology of Chinese Traditional Medicine Lunan Pharmaceutical Group Co.Ltd.LinyiShandong 276000China Institute of Chinese Medicine Sciences Guangdong Pharmaceutical UniversityGuangzhouGuangdong 510006China School of Pharmacy Gomal UniversityD.I.Khan 29220Pakistan School of Pharmacy Shanghai Jiao Tong UniversityShanghai 200240China

Objective To establish gas chromatography-mass spectrometry(GC-MS)fingerprint method for the petroleum ether fraction of Shenqi Jiangtang Granules(SQJTG)and evaluate the product *** The GC-MS fingerprint of petroleum ether fraction of SQJTG was established by GC-MS,and the chemical components corresponding to the fingerprint peaks were structurally identified on *** batch consistency of SQJTG products was evaluated based on the chemical composition of petroleum ether parts by using fingerprint similarity evaluation and principal components analysis(PCA)*** the same time,Hotelling's T2 and DMODX statistics are used to set the control range for the quality of different batches of *** Twenty-two components were identified from the petroleum ether part of SQJTG,accounting for 60.94%of the total components *** similarity of fingerprints of petroleum ether parts of 24 batches of SQJTG was greater than *** PCA of 24 batches of samples were all under the control limits of Hotellin’s T2 and DMODX statistics,indicating that the petroleum ether parts of different batches of SQJTG were *** The developed GC-MS fingerprint method can be used to evaluate the quality of SQJTG.

关键词： Shenqi Jiangtang Granules(SQJTG) Gas chromatography-mass spectrometry(GCMS) Similarity evaluation principal components analysis Quality evaluation

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An Image Steganalysis Method Based on Characteristic Function Moments and PCA

An Image Steganalysis Method Based on Characteristic Functio...

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第三十届中国控制会议

作者： LI Hui,SUN Ziwen,ZHOU Zhiping Institute of Automation,Jiangnan University,Wuxi 214122,P.R.China

＜正＞In this paper,a universal steganalysis scheme is proposed for *** scheme is based on the characteristic function（CF） moments of three-level wavelet subbands including the further decomposition coefficients of the first scale diagonal *** first three statistical moments of each wavelet band of test image and prediction-error image are selected to form 102 dimensional features for *** components analysis（PCA） is utilized to reduce the features and the support vector machine（SVM） is adopted as the *** experimental results show the proposed scheme has good performance in attacking JPHide and JSteg.

关键词： Steganalysis Statistical moments principal components analysis

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Fault Diagnosis analysis with Support Vector Regression and Particle Swarm Optimization Algorithm

Fault Diagnosis Analysis with Support Vector Regression and ...

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2010 Chinese Control and Decision Conference

作者： WenJie Tian,JiCheng Liu Beijing Automation Institute of Beijing Union University,Beijing,China,100101

＜正＞The fault diagnosis model with support vector regression（SVR） and particle swarm optimization algorithm （POSA） for is *** novel structure model has higher accuracy and faster convergence *** construct the network structure,and give the algorithm *** impact factor of fault behaviors is *** the ability of strong self-learning and faster convergence,this fault detection method can detect various fault behaviors rapidly and effectively by learning the typical fault characteristic *** the character that principal components analysis algorithm can keep the discern ability of original dataset after reduction,the reduces of the original dataset are calculated and used to train individual SVR for ensemble,and consequently,increase the detection *** validate the effectiveness of the proposed method,simulation experiments are performed based on the electronic circuit *** results show that the proposed method is a promised method owning to its high diversity,high detection accuracy and faster speed in fault diagnosis.

关键词： Support Vector Regression principal components analysis Fault Diagnosis Reduction Particle Swarm Optimization Algorithm

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Metabolomic difference between blood plasma and serum

Metabolomic difference between blood plasma and serum

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第九届全国药物和化学异物代谢学术会议

作者： LIU Lin-sheng,A Jiye,WANG Guang-ji~*,YAN Bei,ZHANG Ying,WANG Xin-wen,ZHAO Chun-yan, GAO Bei,SHI Jiani,LI Meng-jiei,ZHENG Tian,ZHENG Yuan-ting,ZHOU Fang,SUN Jian-guo Lab of Metabolomics,Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University,Nanjing 21009,Jiangsu,CHINA

AIM:To investigate metabolomic difference between blood plasma and ***:GC/TOFMS was employed to profile their *** components analysis(PCA) was used to process the ***: PCA of the data showed evident difference between *** the 72 authentically identified compounds;29 and 7 metabolites were determined at significantly higher level in serum and plasma,*** samples showed obviously larger variation than serum *** investigate the reason that causes the variances,serum- and plasma-blood from rats were incubated and plasma and serum were analyzed.A continual movement of scores plots was observed along with incubation,and distinct metabolomic variation was shown after shorter incubation(2 h).Generally,the metabolites involved in glycolysis,tricarboxylic acid cycle, and urea cycle were identified to differentiate plasma & serum, and to characterize incubation dependent *** samples clustered closer and serum metabolites underwent less intensive metabolism than ***: The study suggested that blood cells metabolism cause the metabolomic variation;there is great risk to lose the original data by collecting and analyzing prolonged,incubated plasma and *** results facilitate our evaluating the priority of plasma and serum in metabolomic study and the understanding and comparing the data obtained from serum and plasma.

关键词： plasma serum metabolites metabolomics GC/TOFMS principal components analysis

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