Comparative study of different machine learning models in landslide susceptibility assessment: A case study of Conghua District, Guangzhou, China

Machine learning is currently one of the research hotspots in the field of landslide prediction.To clarify and evaluate the differences in characteristics and prediction effects of different machine learning models,Conghua District,which is the most prone to landslide disasters in Guangzhou,was selected for landslide susceptibility evaluation.The evaluation factors were selected by using correlation analysis and variance expansion factor method.Applying four machine learning methods namely Logistic Regression(LR),Random Forest(RF),Support Vector Machines(SVM),and Extreme Gradient Boosting(XGB),landslide models were constructed.Comparative analysis and evaluation of the model were conducted through statistical indices and receiver operating characteristic(ROC)curves.The results showed that LR,RF,SVM,and XGB models have good predictive performance for landslide susceptibility,with the area under curve(AUC)values of 0.752,0.965,0.996,and 0.998,respectively.XGB model had the highest predictive ability,followed by RF model,SVM model,and LR model.The frequency ratio(FR)accuracy of LR,RF,SVM,and XGB models was 0.775,0.842,0.759,and 0.822,respectively.RF and XGB models were superior to LR and SVM models,indicating that the integrated algorithm has better predictive ability than a single classification algorithm in regional landslide classification problems.

A cloud model target damage effectiveness assessment algorithm based on spatio-temporal sequence finite multilayer fragments dispersion

To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.

Accuracy assessment of global vertical displacement loading tide models for the equatorial and Indian Ocean

The three-dimensional displacements caused by ocean loading effects are significant enough to impact spatial geodetic measurements on sub-daily or longer timescales,particularly in the vertical direction.Currently,most tide models incorporate the distribution of vertical displacement loading tides;however,their accuracy has not been assessed for the equatorial and Indian Ocean regions.Global Positioning System(GPS)observations provide high-precision data on sea-level changes,enabling the assessment of the accuracy and reliability of vertical displacement tide models.However,because the tidal period of the K_(2) constituent is almost identical to the orbital period of GPS constellations,the estimation of the K_(2) tidal constituent from GPS observations is not satisfactory.In this study,the principle of smoothness is employed to correct the systematic error in K_(2) estimates in GPS observations through quadratic fitting.Using the adjusted harmonic constants from 31 GPS stations for the equatorial and Indian Ocean,the accuracy of eight major constituents from five global vertical displacement tide models(FES2014,EOT11a,GOT4.10c,GOT4.8,and NAO.99b)is evaluated for the equatorial and Indian Ocean.The results indicate that the EOT11a and FES2014 models exhibit higher accuracy in the vertical displacement tide models for the equatorial and Indian Ocean,with root sum squares errors of 2.29 mm and 2.34 mm,res-pectively.Furthermore,a brief analysis of the vertical displacement tide distribution characteristics of the eight major constituents for the equatorial and Indian Ocean was conducted using the EOT11a model.

A novel refined dynamic model of high-speed maglev train-bridge coupled system for random vibration and running safety assessment

Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations.A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper,in which multi-source uncertainty excitation can be considered simultaneously,and the probability density evolution method(PDEM)is adopted to reveal the system-specific uncertainty dynamic characteristic.The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle,and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges,which are directly established by using finite element method.The model is proven to be applicable by comparing with Monte Carlo simulation.By applying the proposed stochastic framework to the high maglev line,the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment.Moreover,the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated.The results show that the augmentation of train speed will move backward the sensitive wavelength interval,and track irregularity amplitude influences the response remarkably in the sensitive interval.

Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

Purpose-In order to solve the problem of inaccurate calculation of index weights,subjectivity and uncertainty of index assessment in the risk assessment process,this study aims to propose a scientific and reasonable centralized traffic control(CTC)system risk assessment method.Design/methodologylapproach-First,system-theoretic process analysis(STPA)is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis.Then,to enhance the accuracy of weight calculation,the fuzzy analytical hierarchy process(FAHP),fuzzy decision-making trial and evaluation laboratory(FDEMATEL)and entropy weight method are employed to calculate the subjective weight,relative weight and objective weight of each index.These three types of weights are combined using game theory to obtain the combined weight for each index.To reduce subjectivity and uncertainty in the assessment process,the backward cloud generator method is utilized to obtain the numerical character(NC)of the cloud model for each index.The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system.This cloud model is used to obtain the CTC system's comprehensive risk assessment.The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud.Finally,this process yields the risk assessment results for the CTC system.Findings-The cloud model can handle the subjectivity and fuzziness in the risk assessment process well.The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/value-This study provides a cloud model-based method for risk assessment of CTC systems,which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment,achieving effective risk assessment of CTC systems.It can provide a reference and theoretical basis for risk management of the CTC system.

Research on the Assessment System of Computational Mechanics Courses Based on the TOPSIS Entropy Weight Model

This paper takes the assessment and evaluation of computational mechanics course as the background,and constructs a diversified course evaluation system that is student-centered and integrates both quantitative and qualitative evaluation methods.The system not only pays attention to students’practical operation and theoretical knowledge mastery but also puts special emphasis on the cultivation of students’innovative abilities.In order to realize a comprehensive and objective evaluation,the assessment and evaluation method of the entropy weight model combining TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)multi-attribute decision analysis and entropy weight theory is adopted,and its validity and practicability are verified through example analysis.This method can not only comprehensively and objectively evaluate students’learning outcomes,but also provide a scientific decision-making basis for curriculum teaching reform.The implementation of this diversified course evaluation system can better reflect the comprehensive ability of students and promote the continuous improvement of teaching quality.

Product reliability assessment based on proportional hazard degradation model

In order to evaluate the reliability of long-lifetime products with degradation data, a new proportional hazard degradation model is proposed. By the similarity between time-degradation data and stress-accelerated lifetime, and the failure rate function of degradation data which is assumed to be proportional to the time covariate, the reliability assessment based on a proportional hazard degradation model is realized. The least squares method is used to estimate the model＇s parameters. Based on the failure rate of the degradation data and the proportion function of the known time, the failure rate and the reliability function under the given time and the predetermined failure threshold can be extrapolated. A long life GaAs laser is selected as a case study and its reliability is evaluated. The results show that the proposed method can accurately describe the degradation process and it is effective for the reliability assessment of long lifetime products.

Construction of Risk Assessment Application Model of Epidemic Disease in Large-scale Pig Farms

The application model of epidemic disease assessment technology for Web-based large-scale pig farm was expounded from the identification of epidemic disease risk factors, construction of risk assessment model and development of risk assessment system. The assessed pig farm uploaded the epidemic disease risk data information through on-line answering evaluating questionnaire to get the immediate evaluation report. The model could enhance the risk communication between pig farm veterinarian, manager and veterinary experts to help farm system understand and find disease risk factors, assess and report the potential high risk items of the pig farm in the three systems of engineering epidemic disease prevention technology, biological safety and immune monitoring, and promote the improvement and perfection of epidemic disease prevention and control measures.

ON INFORMATION THEORY METHOD FOR RELIABILITY ASSESSMENT OF SYSTEMS CONSISTING OF DIFFERENT SUCCESS FAILURE MODEL UNITS

Using the characteristic of addition of information quantity and the principle of equivalence of information quantity, this paper derives the general conversion formulae of the formation theory method conversion (synthesis) on the systems consisting of different success failure model units. According to the fundamental method of the unit reliability assessment, the general models of system reliability approximate lower limits are given. Finally, this paper analyses the application of the assessment method by examples, the assessment results are neither conservative nor radical and very satisfactory. The assessment method can be popularized to the systems which have fixed reliability structural models.

Correction of Corporation Value Assessment Model Based on Corporate Social Responsibility

The performance of corporate social responsibility is conducive to the con- tinuous improvement of their profitability, and promotes the upgrading of corporation value. However, it is difficult to confirm, calculate and check the costs and benefits brought by the implementation of corporate social responsibility under the current ac- counting theory system, so it is difficult to estimate whether the fulfillment of corpo- rate social responsibility has any effects on the corporation value assessment. Therefore, based on corporate social responsibility, the correction mode of corpora- tion value assessment is put forward.

Machine Learning-Based Decision-Making Mechanism for Risk Assessment of Cardiovascular Disease

Cardiovascular disease(CVD)has gradually become one of the main causes of harm to the life and health of residents.Exploring the influencing factors and risk assessment methods of CVD has become a general trend.In this paper,a machine learning-based decision-making mechanism for risk assessment of CVD is designed.In this mechanism,the logistics regression analysismethod and factor analysismodel are used to select age,obesity degree,blood pressure,blood fat,blood sugar,smoking status,drinking status,and exercise status as the main pathogenic factors of CVD,and an index systemof risk assessment for CVD is established.Then,a two-stage model combining K-means cluster analysis and random forest(RF)is proposed to evaluate and predict the risk of CVD,and the predicted results are compared with the methods of Bayesian discrimination,K-means cluster analysis and RF.The results show that thepredictioneffect of theproposedtwo-stagemodel is better than that of the comparedmethods.Moreover,several suggestions for the government,the medical industry and the public are provided based on the research results.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

Projection pursuit cluster model and its application in water quality assessment

One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must be used. In order to overcome this issues the projection pursuit principle is introduced into water quality assessment, and projection pursuit cluster(PPC) model is developed in this study. The PPC model makes the transition from high dimension to one-dimension. In other words, based on the PPC model, multifactor problem can be converted to one factor problem. The application of PPC model can be divided into four parts: (1) to estimate projection index function Q(); (2) to find the right projection direction ; (3) to calculate projection characteristic value of the i th sample z-i, and (4) to draw comprehensive analysis on the basis of z-i. On the other hand, the empirical formula of cutoff radius R is developed, which is benefit for the model to be used in practice. Finally, a case study of water quality assessment is proposed in this paper. The results showed that the PPC model is reasonable, and it is more objective and less subjective in water quality assessment. It is a new method for multivariate problem comprehensive analysis.

Remaining Useful Life Model and Assessment of Mechanical Products: A Brief Review and a Note on the State Space Model Method

The remaining useful life(RUL) prediction of mechanical products has been widely studied for online system performance reliability, device remanufacturing, and product safety(safety awareness and safety improvement). These studies incorporated many di erent models, algorithms, and techniques for modeling and assessment. In this paper, methods of RUL assessment are summarized and expounded upon using two major methods: physics model based and data driven based methods. The advantages and disadvantages of each of these methods are deliberated and compared as well. Due to the intricacy of failure mechanism in system, and di culty in physics degradation observation, RUL assessment based on observations of performance variables turns into a science in evaluating the degradation. A modeling method from control systems, the state space model(SSM), as a first order hidden Markov, is presented. In the context of non-linear and non-Gaussian systems, the SSM methodology is capable of performing remaining life assessment by using Bayesian estimation(sequential Monte Carlo). Being e ective for non-linear and non-Gaussian dynamics, the methodology can perform the assessment recursively online for applications in CBM(condition based maintenance), PHM(prognostics and health management), remanufacturing, and system performance reliability. Finally, the discussion raises concerns regarding online sensing data for SSM modeling and assessment of RUL.

Relationship between modified homeostasis model assessment/correlative serum factors and diabetic retinopathy among type 2 diabetics with insulin therapy in Guangzhou, China

AIM:To explore the related risk factors for diabetic retinopathy(DR)in type 2 diabetes with insulin therapy.METHODS:We studied the relationships among blood glucose,serum C-peptide,plasma insulin,beta-cell function and the development of DR.Beta-cell function was assessed by a modified homeostasis model assessment(modified HOMA)which was gained by using C-peptide to replace insulin in the homeostasis model assessment(HOMA)of beta-cell function.We also studied the relationships between modified HOMA index and serum C-peptide response to 100 g tasteless steamed bread to determine the accuracy of modified HOMA.RESULTS:Our study group consisted of 170 type 2diabetic inpatients with DR(age:58.35±13.87y,mean±SD)and 205 type 2 diabetic inpatients with no DR(NDR)(age:65.52±11.59y).DR patients had higher age,longer diabetic duration,higher hypertension grade,higher postprandial plasma glucose,higher fluctuation level of plasma glucose,lower body mass index(BMI),lower postprandial serum insulin and C-peptide,lower fluctuation level of serum insulin and C-peptide(P【0.05).In our logistic regression model,duration of diabetes,hypertension grade,fasting plasma insulin and glycosylated hemoglobin(HbA1C)were significantly associated with the presence of DR after adjustment for confounding factors(P【0.05).CONCLUSION:Our results suggested although modified HOMA showed significant correlation to the occurrence of DR on Spearman’s rank-correlationanalysis,logistic regression showed no significant association between these two variables after adjustment for relevant confounding factors(such as age,sex,duration of diabetes,BMI,hypertension grade,HbA1C,plasma insulin).Duration of diabetes,hypertension grade,fasting plasma insulin and HbA1C were independently associated with the development of DR in Chinese type 2 diabetics.

Recommending the IHACRES model for water resources assessment and resolving water conflicts in Africa

The International Association of Hydrological Sciences （IAHS） recognized the lack of hydro- logical data as a world-wide problem in 2002 and adopted the Prediction of Ungauged Basins （PUB） as a decadal research agenda during the period of 2003 to 2012. One of the objectives is to further develop methodologies for prediction in ungauged basins and to reduce uncertainties in model prediction. Estimation of stream flows is required for flood control, water quality control, valley habitat assessment and water budget of a country. However, the majority of water catchments, streams and valleys are ungauged in most developing countries. The main objective of this paper is to introduce the IHACRES （Identification of Hy- drographs and Components from Rainfall, Evaporation and Stream） model into African hydrological plan- ning as a methodology for water resources assessment, which in turn can be used to resolve water conflicts between communities and countries and to study the climate change issues. This is because the IHACRES model is applied for the estimation of flows in ungauged catchments whose physical catchments descriptors （PCDs） can be determined by driving variables （i.e. rainfall and temperature）; and also in gauged streams but whose gauging stations are no longer operational but historical data are available for model calibration. The model provides a valuable insight into the hydrologic behaviour of the upper water sources for valleys as well as provides a useful methodology for water resources assessment in situations of scarce financial resources in developing countries. In addition, it requires relatively few parameters in its calibration and has been successful applied in previous regionalization studies. It will also make possible the equitable distri- bution of water resources in international basins and rivers＇ catchments. This paper does not apply the model anywhere, but recommends it as a methodology for water resources assessment in order to cure water conflicts on the African continent.

Human Health Risk Assessment Model of Organic Pollution in Groundwater:Shijiazhuang Industrial Zone

In this study, a risk-based management model is developed and applied to an industrial zone. The models proposed by the United States Environmental Protection Agency and Han Bing have been improved by adding a residual ratio of volatile organic compounds （VOC） after boiling and deleting the related parameters in half-life. Using this improved model, an integrated process was used to assess human health risk level in the study area. Compared with water quality analysis, the results highlight the importance of applying an integrated approach for decision making on risk levels and water protection. The results of this study demonstrated that： （1） Compared with these permissible level standards in China （GB 3838-2002） and National Primary Drinking Water Regulations of the United States, the residents＇ daily life had not been affected by the groundwater in this area （except for relative bad water quality of HB3-4 and HB3-6）; （2） The typical detected organic contaminants of all groundwater samples were chloroform, carbon tetrachloride, trichloroethylene and tetrachloroethene, and the pollution sources were mainly industrial sources by preliminary investigations; （3） As for groundwater, the non-carcinogenic risk values of all samples do not exceed the permissible level of 1.0 and the carcinogenic risk values are relatively lower than the permissible level of 1.00E-06 to 1.00E-04; （4） Drinking water pathway of trichloroethylene and tetrachloroethylene mainly contribute to increasing the health risk of residents＇ in study areas; （5） In terms of non-carcinogenic risk and carcinogenic risk, the health risk order for drinking water pathway and dermal contact pathway was： drinking water pathway 〉 dermal contact pathway.

Aquaculture area extraction and vulnerability assessment in Sanduao based on richer convolutional features network model

Sanduao is an important sea-breeding bay in Fujian,South China and holds a high economic status in aquaculture.Quickly and accurately obtaining information including the distribution area,quantity,and aquaculture area is important for breeding area planning,production value estimation,ecological survey,and storm surge prevention.However,as the aquaculture area expands,the seawater background becomes increasingly complex and spectral characteristics differ dramatically,making it difficult to determine the aquaculture area.In this study,we used a high-resolution remote-sensing satellite GF-2 image to introduce a deep-learning Richer Convolutional Features(RCF)network model to extract the aquaculture area.Then we used the density of aquaculture as an assessment index to assess the vulnerability of aquaculture areas in Sanduao.The results demonstrate that this method does not require land and water separation of the area in advance,and good extraction can be achieved in the areas with more sediment and waves,with an extraction accuracy>93%,which is suitable for large-scale aquaculture area extraction.Vulnerability assessment results indicate that the density of aquaculture in the eastern part of Sanduao is considerably high,reaching a higher vulnerability level than other parts.

Dynamic Assessment on Regional Eco-environmental Quality Using AHP-Statistics Model—A Case Study of Chaohu Lake Basin

An indicator system closely connected with eco-environment, in which indicator involves in such fields as society, economy, resources, environment and ecology, is first proposed for eco-environmental quality assessment. Then, a hierarchical model with four levels is established by virtue of these indicators and attributes. In the model, weights of indicators and attributes are determined by combining Delphi method with the Analytic Hierarchy Process (AHP) and a statistic method is used to eliminate the influences arising from the differences in dimension and magnitude of indicators. On these grounds, an AHP-statistics model is provided for regional eco-environmental quality assessment. As a case, such AHP-statistics model is utilized in the dynamic analysis of regional eco-environmental assessment in Chaohu Lake basin. Study results show that natural environmental quality in the watershed was in the declining state while social environmental quality was in a markedly improved situation from 1996, and the synthetic eco-environmental quality was gradually and slowly improved under the common influences of both natural and social environmental factors. Example of application testified the capacities of above methodology to evaluate the real and dynamic state of regional eco-environmental quality.

Application of a Novel Method for Machine Performance Degradation Assessment Based on Gaussian Mixture Model and Logistic Regression

The currently prevalent machine performance degradation assessment techniques involve estimating a machine＇s current condition based upon the recognition of indications of failure features,which entail complete data collected in different conditions.However,failure data are always hard to acquire,thus making those techniques hard to be applied.In this paper,a novel method which does not need failure history data is introduced.Wavelet packet decomposition（WPD） is used to extract features from raw signals,principal component analysis（PCA） is utilized to reduce feature dimensions,and Gaussian mixture model（GMM） is then applied to approximate the feature space distributions.Single-channel confidence value（SCV） is calculated by the overlap between GMM of the monitoring condition and that of the normal condition,which can indicate the performance of single-channel.Furthermore,multi-channel confidence value（MCV）,which can be deemed as the overall performance index of multi-channel,is calculated via logistic regression（LR） and that the task of decision-level sensor fusion is also completed.Both SCV and MCV can serve as the basis on which proactive maintenance measures can be taken,thus preventing machine breakdown.The method has been adopted to assess the performance of the turbine of a centrifugal compressor in a factory of Petro-China,and the result shows that it can effectively complete this task.The proposed method has engineering significance for machine performance degradation assessment.