Predicting the growth performance of growing-finishing pigs based on net energy and digestible lysine intake using multiple regression and artificial neural networks models

Backgrounds:Evaluating the growth performance of pigs in real-time is laborious and expensive,thus mathematical models based on easily accessible variables are developed.Multiple regression(MR)is the most widely used tool to build prediction models in swine nutrition,while the artificial neural networks(ANN)model is reported to be more accurate than MR model in prediction performance.Therefore,the potential of ANN models in predicting the growth performance of pigs was evaluated and compared with MR models in this study.Results:Body weight(BW),net energy(NE)intake,standardized ileal digestible lysine(SID Lys)intake,and their quadratic terms were selected as input variables to predict ADG and F/G among 10 candidate variables.In the training phase,MR models showed high accuracy in both ADG and F/G prediction(R^(2)_(ADG)=0.929,R^(2)_(F/G)=0.886)while ANN models with 4,6 neurons and radial basis activation function yielded the best performance in ADG and F/G prediction(R^(2)_(ADG)=0.964,R^(2)_(F/G)=0.932).In the testing phase,these ANN models showed better accuracy in ADG prediction(CCC:0.976 vs.0.861,R^(2):0.951 vs.0.584),and F/G prediction(CCC:0.952 vs.0.900,R^(2):0.905 vs.0.821)compared with the MR models.Meanwhile,the“over-fitting”occurred in MR models but not in ANN models.On validation data from the animal trial,ANN models exhibited superiority over MR models in both ADG and F/G prediction(P<0.01).Moreover,the growth stages have a significant effect on the prediction accuracy of the models.Conclusion:Body weight,NE intake and SID Lys intake can be used as input variables to predict the growth performance of growing-finishing pigs,with trained ANN models are more flexible and accurate than MR models.Therefore,it is promising to use ANN models in related swine nutrition studies in the future.

Correlation Analysis of Fiscal Revenue and Housing Sales Price Based on Multiple Linear Regression Model

This paper selects seven indicators of financial revenue and housing sales price in recent 19 years in China,and uses SPSS and Excel to carry out descriptive statistics,independent sample t-test,correlation analysis and regression analysis to comprehensively study the correlation between financial revenue and housing sales price in China,and establishes the relationship between financial revenue and housing sales price When the average selling price of commercial housing increases by one unit,the fiscal revenue will increase by 27.855 points.

Modeling the Undrained Shear Strength with Soil Index Properties for Niger Delta Soft Clays

The aim of this study was to model the Undrained Shear Strength (USS) of soil found in the coastal region of the Niger Delta in Nigeria with some soil properties. The undrained shear strength (USS) is a key parameter needed for most geotechnical/structural designs. Accurate determination of the USS of soft clays can be challenging to obtain in the laboratory due to the difficulty in remoulding the clay to its in-situ conditions before testing and more accurate test such as Cone Penetration test (CPT) can be quite expensive. This study was carried out at Escravos site which is located in Delta state, Nigeria. Three Boreholes were drilled and soil samples were collected at 0.75 m intervals up to a depth of 45 m. Laboratory tests were used to obtain the moisture content, bulk unit weight, liquid and plastic limit, while CPT was used in obtaining the undrained shear strength. Classification of the soil samples was done by adopting the Unified Soil Classification System and various models relating the USS with the soil properties were developed. The result showed that most of the soils at Escravos site were predominately inorganic clay of high plasticity which are problematic due to the expansion and shrinking nature of this type of soil. The model developed showed that the soil properties that gave the best fit with the USS were the moisture content and effective stress of the soil. The coefficient of determination (R2) and the root mean square error (RMSE) obtained for this model were 0.805 and 6.37 KN/m2, respectively.

Development of Empirical Models for the Estimation of CBR Value of Soil from Their Index Properties: A Case Study of the Ogbia-Nembe Road in Niger Delta Region of Nigeria

This study developed empirical-mathematical models to predict the California Bearing Ratio (CBR) using soil index properties in Ogbia-Nembe road in the Niger Delta region of Nigeria. The determination of CBR of soil is a laborious operation that requires a longer time and materials leading to increased cost and schedule;this can be reduced by adopting an empirical-mathematical model that can predict the CBR using other simpler soil index properties such as Plastic Limit (PL), the Liquid Limit (LL), the Plasticity Index (PI) and the Moisture Content (MC), which are less laborious and take lesser time to obtain. Thirteen models were developed to understand the relationship between these soil index properties: the independent variable and the California Bearing Ratio (CBR): the dependent variable;Six linear, Six quadratic and One multiple linear regression models were developed for this relationship. Analysis of variance (ANOVA) on the thirteen models showed that the Optimum Moisture Content (OMC) and the Maximum Dry Density (MDD) are better independent variables for the prediction of the CBR value of Ogbia-Nembe soil generating a quadratic model and a multiple linear regression model having a better coefficient of determination R2 = 0.96 and 0.94 respectively, mean square error (MSE) of 0.74 and 1.152 respectively with Root mean square errors of 0.861 and 1.073 accordingly. These models were used to predict the CBR of the soil. The CBR values predicted by the model were further compared with those of the actual experimental test and found to be relatively consistent with minimal variance. This establishes that CBR of any soil can be predicted from the Index Property of the soil and this is more economical and takes lesser time and can be universally adopted for soil investigation.

Multiple linear regression models of urban runoff pollutant load and event mean concentration considering rainfall variables

Rainfall is an important factor in estimating the event mean concentration （EMC） which is used to quantify the washed-off pollutant concentrations from non-point sources （NPSs）. Pollutant loads could also be calculated using rainfall, catchment area and runoff coefficient. In this study, runoff quantity and quality data gathered from a 28-month monitoring conducted on the road and parking lot sites in Korea were evaluated using multiple linear regression （MLR） to develop equations for estimating pollutant loads and EMCs as a function of rainfall variables. The results revealed that total event rainfall and average rainfall intensity are possible predictors of pollutant loads. Overall, the models are indicators of the high uncertainties of NPSs; perhaps estimation of EMCs and loads could be accurately obtained by means of water quality sampling or a long term monitoring is needed to gather more data that can be used for the development of estimation models.

Analyzing geomorphological and topographical controls for the heterogeneous glacier mass balance in the Sikkim Himalayas

Glacier response patterns at the catchment scale are highly heterogeneous and defined by a complex interplay of various dynamics and surface factors.Previous studies have explained heterogeneous responses in qualitative ways but quantitative assessment is lacking yet where an intrazone homogeneous climate assumption can be valid.Hence,in the current study,the reason for heterogeneous mass balance has been explained in quantitative methods using a multiple linear regression model in the Sikkim Himalayan region.At first,the topographical parameters are selected from previously published studies,then the most significant topographical and geomorphological parameters are selected with backward stepwise subset selection methods.Finally,the contributions of selected parameters are calculated by least square methods.The results show that,the magnitude of mass balance lies between-0.003±0.24 to-1.029±0.24 m.w.e.a^(-1) between 2000 and 2020 in the Sikkim Himalaya region.Also,the study shows that,out of the terminus type of the glacier,glacier area,debris cover,ice-mixed debris,slope,aspect,mean elevation,and snout elevation of the glaciers,only the terminus type and mean elevation of the glacier are significantly altering the glacier mass balance in the Sikkim Himalayan region.Mathematically,the mass loss is approximately 0.40 m.w.e.a^(-1) higher in the lake-terminating glaciers compared to the land-terminating glaciers in the same elevation zone.On the other hand,a thousand meters mean elevation drop is associated with 0.179 m.w.e.a-1of mass loss despite the terminus type of the glaciers.In the current study,the model using the terminus type of the glaciers and the mean elevation of the glaciers explains 76% of fluctuation of mass balance in the Sikkim Himalayan region.

Economic modeling of mechanized and semi-mechanized rainfed wheat production systems using multiple linear regression model

Mathematical modeling of economic indices is a challenging topic in crop production systems.The present study aimed to model the economic indices of mechanized and semimechanized rainfed wheat production systems using various multiple linear regression models.The study area was Behshahr County located in the east of Mazandaran Province,Northern Iran.The statistical population included all wheat producers in Behshahr County in 2016/17 crop year.Five input variables were human labor,machinery,diesel fuel,chemical(chemical fertilizers and chemical pesticides)costs,and the income was considered to be the output.The results showed that the cost of wheat production in the semimechanized system was higher than that of the mechanized system.In both systems,the highest cost was related to agricultural machinery input.Moreover,seed cost was lower in the mechanized system than that of the semi-mechanized system.The net return indicator was 993.68$ha1 and 626.71$ha1 for the mechanized and semi-mechanized systems,respectively.The average benefit to cost ratio was 3.46 and 2.40 for the mechanized and semi-mechanized systems,respectively,demonstrating the greater profitability of the mechanized system.The results of the evaluation of five types of regression models including the Cobb-Douglas,linear,2FI,quadratic and pure-quadratic for the mechanized and semi-mechanized production systems indicated that in the developed Cobb-Douglas model,the R2-value was higher than that of the quadratic model while RMSE and MAPE of the quadratic model were determined to be smaller than that of the Cobb-Douglas model.Therefore,the best model to investigate the relationship between input costs and the income of wheat production in both mechanized and semi-mechanized systems was the quadratic model.

The interaction between stratospheric monthly mean regional winds and sporadic-E

In the present study, a statistical investigation is carried out to explore whether there is a relationship between the critical frequency （foEs） of the sporadic-E layer that is occasionally seen on the E region of the ionosphere and the quasi- biennial oscillation （QBO） that flows in the east-west direction in the equatorial stratosphere. Multiple regression model as a statistical tool was used to determine the relationship between variables. In this model, the stationarity of the variables （foEs and QBO） was firstly analyzed for each station （Cocos Island, Gibilmanna, Niue Island, and Tahiti）. Then, a co- integration test was made to determine the existence of a long-term relationship between QBO and foes. After verifying the presence of a long-term relationship between the variables, the magnitude of the relationship between variables was further determined using the multiple regression model. As a result, it is concluded that the variations in foEs were explainable with QBO measured at 10 hPa altitude at the rate of 69%, 94%, 79%, and 58% for Cocos Island, Gibilmanna, Niue Island, and Tahiti stations, respectively. It is observed that the variations in foes were explainable with QBO measured at 70 hPa altitude at the rate of 66%, 69%, 53%, and 47% for Cocos Island, Gibilmanna, Niue Island, and Tahiti stations, respectively.

Cyperus papyrus L. Growth Rate and Mortality in Relation to Water Quantity, Quality and Soil Characteristics in Nyando Floodplain Wetland, Kenya

Cyperus papyrus (L.) growth rate and mortality is influenced by environmental conditions prevailing in the wetland. To assess growth dynamics of C. papyrus in relation to water depth and anthropogenic (exploitation) pressures, monthly and bi-monthly measurement of culm length and girth were done between June and December 2010 (period 1) and April to June 2011 (period 2). Three study sites were selected based on the water levels and livelihood-driven exploitation pressures. Surrogate measurements of individual culm height and girth were done in three 1 m2 quadrats in each site to determine the growth rate of papyrus. Water depth was lowest in period 2 (dry) and highest in period 1 (wet) which was related to the livelihood activities being highest in period two and lowest in period one. Culm mortality occurred throughout the study period with 64% due to natural senescing while insect/rodent accounted for 19%. Papyrus growth was higher in Singida (2.5 ± 0.2 cm/day) representing less disturbed site and least in Wasare (1.4 ± 0.1 cm/day) which was highly disturbed. Multiple regression models for culm length showed culm density, mean length and NH4 negatively influenced growth rate while site as a dummy variable, water depth, SRP and TP had positive effects on papyrus growth rate. Understanding growth rate and causes of mortality in papyrus is important to establish sustainable management strategies of this ecosystem to maintain its integrity.

Research on China’s Population Structure in the New Situation

To analyze the impact of the“two-child policy”on the population size and structure,first of all,the birth rate,the ratio of men and women,and the ratio of urban and rural population are used as indicators.Before and after the dispersion,then establish a PDE model,and compare it with the population predicted by the gray forecast to analyze the mitigation of the ageing of the second child policy;continue to analyze the impact of changes in the population structure on the national economy,and select the male and female ratio and the labor population The urban-rural population ratio is used as an index to establish a multiple regression equation for analysis,and a related regression equation is obtained.Finally,the future marriage problem is analyzed,considering only the difference in the number of men and women entering the marriageable period at the same time.The difference in the number of marriageable populations is analyzed through the difference in the number of men and women born at birth,focusing on a dynamic perspective.

Flood Generation Mechanisms and Potential Drivers of Flood in Wabi-Shebele River Basin, Ethiopia

Flood is a natural process generated by the interaction of various driving factors. Flood peak flows, flood frequency at different return periods, and potential driving forces are analyzed in this study. The peak flow of six gauging stations, with a catchment area ranging from 169 - 124,108 km2 and sufficient observed streamflow data, was selected to develop threshold (3rd quartile) magnitude and frequency (POTF) that occurred over ten years of records. Sixteen Potential climatic, watershed and human driving factors of floods in the study area were identified and analyzed with GIS, Pearson’s correlation, and Principal Correlation Analysis (PCA) to select the most influential factors. Eight of them (MAR, DA, BE, VS, sand, forest AGR, PD) are identified as the most significant variables in the flood formation of the basin. Moreover, mean annual rainfall (MAR), drainage area (DA), and lack of forest cover are explored as the principal driving factors for flood peak discharge in Wabi-Shebele River Basin. Finally, the study resulted in regression equations that helped plan and design different infrastructure works in the basin as ungauged catchment empirical equations to compute QMPF, Q5, Q10, Q50, and Q100 using influential climate, watershed, and human driving factors. The results of these empirical equations are also statistically accepted with a high significance correlation (R2 > 0.9).

Dew amount and its long-term variation in the Kunes River Valley,Northwest China

Dew is an essential water resource for the survival and reproduction of organisms in arid and semi-arid regions.Yet estimating the dew amount and quantifying its long-term variation are challenging.In this study,we elucidate the dew amount and its long-term variation in the Kunes River Valley,Northwest China,based on the measured daily dew amount and reconstructed values(using meteorological data from 1980 to 2021),respectively.Four key results were found:(1)the daily mean dew amount was 0.05 mm during the observation period(4 July-12 August and 13 September-7 October of 2021).In 35 d of the observation period(i.e.,73%of the observation period),the daily dew amount exceeded the threshold(>0.03 mm/d)for microorganisms;(2)air temperature,relative humidity,and wind speed had significant impacts on the daily dew amount based on the relationships between the measured dew amount and meteorological variables;(3)for estimating the daily dew amount,random forest(RF)model outperformed multiple linear regression(MLR)model given its larger R^(2) and lower MAE and RMSE;and(4)the dew amount during June-October and in each month did not vary significantly from 1980 to the beginning of the 21^(st) century.It then significantly decreased for about a decade,after it increased slightly from 2013 to 2021.For the whole meteorological period of 1980-2021,the dew amount decreased significantly during June-October and in July and September,and there was no significant variation in June,August,and October.Variation in the dew amount in the Kunes River Valley was mainly driven by relative humidity.This study illustrates that RF model can be used to reconstruct long-term variation in the dew amount,which provides valuable information for us to better understand the dew amount and its relationship with climate change.

Parker Test for Heteroskedasticity Based on Sample Fitted Values

To address the drawbacks of the traditional Parker test in multivariate linear models: the process is cumbersome and computationally intensive, we propose a new heteroscedasticity test. A new heteroskedasticity test is proposed using the fitted values of the samples as new explanatory variables, reconstructing the regression model, and giving a new heteroskedasticity test based on the significance test of the coefficients, it is also compared with the existing Parker test which is improved using the principal component idea. Numerical simulations and empirical analyses show that the improved Parker test with the fitted values of the samples proposed in this paper is superior.

An empirical analysis on community residents' perception and major influencing factors of rural tourism development

With the rapid development of rural tourism in China,community residents,as important stakeholders in the development of rural tourism,their perceptions and attitudes directly affect the sustainable and healthy development of local rural tourism.Taking the community residents of Xiaogucheng Village in Hangzhou as the research object,using the methods of field interviews and questionnaires,a multiple regression model was established to conduct an empirical analysis on the perception and main factors affecting the development of rural tourism of community residents.The results show that the development of rural tourism in villages with better economic development is not as popular as expected;Where community residents have made ideological progress and are willing to participate in tourism development,the development effect of rural tourism is remarkable;In addition,community residents also hope that their personal abilities can be combined with rural tourism for common development;The destruction of community environment has a slight impact on the development of rural tourism,which shows that the attention is not enough.Finally,based on the analysis conclusion,it provides new ideas and inspiration for the sustainable development of rural tourism:improving the community residents’participation in rural tourism system,establishing the guidance mechanism of community residents’tourism vocational education,and consolidating the achievements of community ecological environment management.

Analysis of the Relationship Between Railway and Highway Transportation and China's Economic Development

China has a vast land area and frequent interconnections between various regions.China's transportation industry is faced with tremendous pressure.This article combines China’s railway and highway transportation conditions to predict China’s economic development,uses stepwise regression to screen explanatory variables,and finally determines railway passenger turnover,road freight volume and passenger car ownership as the explanatory variables,and GDP as the dependent variable,and also analyzes China’s economic development by establish ing a multiple regression model.

Unconfined compressive strength and failure behaviour of completely weathered granite from a fault zone

Understanding the strength characteristics and deformation behaviour of the tunnel surrounding rock in a fault zone is significant for tunnel stability evaluation.In this study,a series of unconfined compression tests were conducted to investigate the mechanical characteristics and failure behaviour of completely weathered granite(CWG)from a fault zone,considering with height-diameter(h/d)ratio,dry densities(ρd)and moisture contents(ω).Based on the experimental results,a regression mathematical model of unconfined compressive strength(UCS)for CWG was developed using the Multiple Nonlinear Regression method(MNLR).The research results indicated that the UCS of the specimen with a h/d ratio of 0.6 decreased with the increase ofω.When the h/d ratio increased to 1.0,the UCS increasedωwith up to 10.5%and then decreased.Increasingρd is conducive to the improvement of the UCS at anyω.The deformation and rupture process as well as final failure modes of the specimen are controlled by h/d ratio,ρd andω,and the h/d ratio is the dominant factor affecting the final failure mode,followed byωandρd.The specimens with different h/d ratio exhibited completely different fracture mode,i.e.,typical splitting failure(h/d=0.6)and shear failure(h/d=1.0).By comparing the experimental results,this regression model for predicting UCS is accurate and reliable,and the h/d ratio is the dominant factor affecting the UCS of CWG,followed byρd and thenω.These findings provide important references for maintenance of the tunnel crossing other fault fractured zones,especially at low confining pressure or unconfined condition.

Parameter Optimization via Orthogonal Experiment to Improve Accuracy of Metakaolin Ceramics Fabricated by Direct Ink Writing

Kaolin/metakaolin-insulating ceramic components fabricated using direct ink writing(DIW)have important ap-plication prospects in architecture and aerospace.The accuracy of the entire process including the forming and sintering accuracy of ceramics greatly limits the application scope,and high-accuracy ceramic samples can meet the usage requirements in many scenarios.The orthogonal experiment was designed with four process parame-ters,including nozzle internal diameter,filling rate,printing layer height/nozzle internal diameter,and printing speed,to investigate the evolution of the DIW forming accuracy,sintering shrinkage rate and surface roughness of metakaolin-based ceramics with different process parameters.The influence of each process parameter and its mechanism were analyzed to obtain the DIW parameters for high-accuracy metakaolin ceramics.Multiple linear regression models between the dimensional change rate,surface roughness,and process parameters of the ceramic samples were established and validated.The results show that comprehensively considering the forming accuracy of the ceramic green bodies,sintering shrinkage rate and surface roughness,the optimal DIW process parameters were a 0.41 mm nozzle internal diameter,100%filling rate,50%printing layer height/nozzle inter-nal diameter,and a 15 mm/s printing speed.Multiple linear regression models were developed for the process parameters and the printing accuracy,sintering shrinkage rate and surface roughness.The error rates between the theoretical results obtained by substituting the optimal process parameters into the multiple linear regression models and the actual results obtained by printing the samples with the optimal parameters were extremely small,all less than 0.8%.This verified the correctness and predictability of the multiple linear regression models.This work provides a reference basis for rapid fabrication of high-accuracy ceramics via DIW and accuracy prediction with different process parameters.

Spatio-temporal variation in China's climatic seasons from 1951 to 2017

In this paper,meteorological industry standard,daily mean temperature,and an improved multiple regression model are used to calculate China's climatic seasons,not only to help understand their spatio-temporal distribution,but also to provide a reference for China's climatic regionalization and crop production.It is found that the improved multiple regression model can accurately show the spatial distribution of climatic seasons.The main results are as follows.There are four climatic seasonal regions in China,namely,the perennial-winter,no-winter,no-summer and discernible regions,and their ranges basically remained stable from 1951 to 2017.The cumulative anomaly curve of the four climatic seasonal regions clarifies that the trend of China's climatic seasonal regions turned in 1994,after which the area of the perennial-winter and no-summer regions narrowed and the no-winter and discernible regions expanded.The number of sites with significantly reduced winter duration is the largest,followed by the number of sites with increased summer duration,and the number of sites with large changes in spring and autumn is the least.Spring advances and autumn is postponed due to the shortened winter and lengthened summer durations.Sites with significant change in seasonal duration are mainly distributed in Northwest China,the Sichuan Basin,the Huanghe-Huaihe-Haihe(Huang-Huai-Hai) Plain,the Northeast China Plain,and the Southeast Coast.

Sustainable growth research–A study on the telecom operators in China

In recent years,the telecom industry has faced digital transformation challenges and fierce market competition.The challenges push telecom operators to grow their subscriber bases by offering lower prices and improved services and new features,which puts pressure on operators’profitability.In addition,the rise of Internet companies gradually erodes the profit of the traditional telecom operators.Therefore,paying attention to the critical factors impacting firm sustainable growth can help operators get out of the predicament.Based on the resource-based view(RBV),this study explores the factors that influence the firm sustainable growth.Multiple regression model is applied to empirically test the hypotheses with longitudinal time-series panel data from major telecom operators in China.The study provides empirical evidence for sustainable growth research and useful insights for practitioners on the way to keep sustainable growth.

Prediction of Extractable Cd,Pb and Zn in Contaminated Woody Habitat Soils Using a Change Point Detection Method

Accumulation of heavy metals in soils poses a potential risk to plant production, which is related to availability of the metals in soil. The phytoavailability of metals is usually evaluated using extracting solutions such as salts, acids or chelates. The purpose of this study was to identify the most significant soil parameters that can be used to predict the concentrations of acetic and citric acidextractable cadmium(Cd), lead(Pb) and zinc(Zn) in contaminated woody habitat topsoils. Multiple linear regression models were established using two analysis strategies and three sets of variables based on a dataset of 260 soil samples. The performance of these models was evaluated using statistical parameters. Cation exchange capacity, CaCO_3, organic matter, assimilated P, free Al oxide,sand and the total metal concentrations appeared to be the main soil parameters governing the solubility of Cd, Pb and Zn in acetic and citric acid solutions. The results strongly suggest that the metal solubility in extracting solutions is extractable concentrationdependent since models were overall improved by incorporating a change point. This change point detection method was a powerful tool for predicting extractable Cd, Pb and Zn. Suitable predictions of extractable Cd, Pb and Zn concentrations were obtained, with correlation coefficient(adjusted r) ranging from 0.80 to 0.99, given the high complexity of the woody habitat soils studied. Therefore,the predictive models can constitute a decision-making support tool for managing phytoremediation of contaminated soils, making recommendations to control the potential bioavailability of metals. The relationships between acetic and/or citric acid-extractable concentrations and the concentrations of metals into the aboveground parts of plants need to be predicted, in order to make their temporal monitoring easier.