Statistical Linearization Method Research Articles

The impact of entrepreneurial ecosystems on digital transformations: micro-level analysis

Purpose Entrepreneurial ecosystems (EEs) contribute to organisational success through enabling actors to restructure businesses, stimulating exchanges of resources as well as applications and improvements to technological approaches. Hence, the purpose of this paper is to study the impact of EE micro-level variables on digital transformations. Design/methodology/approach Based on data spanning 5,000 Portuguese firms, the authors selected a random sample of 300, including businesses in the industrial, retail and service sectors. The authors deployed the multiple linear regression statistical method to validate the hypotheses. Findings As a result, the authors may conclude the organisation and the micro-level actors of EEs, owners and their members of staff produce influences on digital transformation processes. Originality/value This study contributes to completing the gap in the literature regarding the shortage of quantitative empirical studies approaching micro-level EE variables from the perspective of their relationships with digital transformation processes.

Wind-Induced Dynamic Response of Inter-Story Isolated Tall Buildings with Friction Pendulum Bearing Based on an Enhanced Simplified Model

Isolation technology, especially for base isolation, is increasingly being applied in earthquake-prone areas. To satisfy some special demands (such as prevention from seawater erosion of an isolation layer, story-adding retrofit of existing buildings, avoidance of collision between base-isolated tall buildings, and so on), the isolation layer sometimes has to be set in the middle of a building to constitute inter-story isolated buildings. This special structural form inevitably encounters strong wind loads during service life, and its wind-resistant performance deserves to be investigated. This study conducts the wind-induced vibration analysis of inter-story isolated tall buildings with friction pendulum bearing (FPB). The nonlinear time domain analysis model and statistical linearization method to compute the wind-induced response of FPB inter-story isolated tall buildings are addressed based on an enhanced simplified model. Considering the independence of the upper and lower structures, two structural design schemes for inter-story isolated tall buildings are provided. Their dynamic characteristics are analyzed, and wind-induced responses are compared. Finally, the accuracy of the statistical linearization method is verified. This study provides an important theoretical basis for the structural design and wind resistance of inter-story isolated tall buildings.

Improved Autuoformer Electricity load forecasting based on model fusion

The development of the power system is undergoing rapid changes. The future direction of power system development is inevitably smart grids. This paper proposes an optimization of the Autoformer model based on model fusion to improve the accuracy of electricity load forecasting. By incorporating the predictive results of traditional statistical multivariate linear regression (MLR) and machine learning method LightGBM into the Autoformer model, we aim to fully leverage the strengths of both traditional statistical and machine learning approaches to enhance the predictive accuracy of the Autoformer model. Experimental results, using mean MAE and MSE as the evaluation metrics, demonstrate that the algorithm proposed in this paper exhibits better performance in the prediction results.

Analisis Model Tarikan Pergerakan Sekolah Di Kota Palangka Raya

The school zone is a land use that can create the trip attraction. The purpose of this study is to model the trip attraction and to analysis the factors that most influence attraction to the Catholic school area in Palangka Raya. The study was conducted at four schools in one zone. Primary data, i.e. the number of vehicles entering the school premises, was obtained through direct observation in the target schools. Secondary data was obtained through documentation and interviews with the operators of the schools. The collected data was analysed using the linear regression statistical method assisted by SPSS software version 25. All variables involved, i.e. number of students, number of teachers, number of school benches, class capacity and class area, are strongly correlated with the variable 'traffic volume'. From the linear regression analysis, the number of students is the independent variable that is highly correlated and significantly influence the trip attraction, as shown by the value of r=0.99 and R2 = 0.998. The model of physical activity attractiveness in this study is Y = -10.686 + 0.934X1. The results of this study contribute to education field especially in transportation, as they support the theory that the number of students significantly influences the trip attraction in school land use

System with nano piezoengine under randomly influences for biomechanics

The sufficient condition of absolute stability system with nano piezoengine by using the derivative of the hysteretic piezoengine deformation is determined for the randomly influences. The set of equilibrium positions of the piezoengine in the control system is stable relative to mathematical expectations, when the condition of absolute stability with the maximum piezo module is met. The statistical linearization method is using for the determination condition of absolute stability control system with the nano piezoengine.

The Role of Debt to Ratio and Profitability in Economic Growth and Company Development

This study analyses the relationship and influence of Debt Asset Ratio (DAR) on company profitability. The data used in this study were obtained from the financial reports of companies listed on the Indonesia Stock Exchange during 2018-2022. The analytical method used is simple linear regression using statistical software. The steps are planning, collecting, analyzing, and interpreting data to answer research questions. DAR and profitability as variables in this study, population, and samples from 6 companies for five years. The influence of Debt to Asset Ratio applied to Company Profitability was analyzed using the linear regression statistical method. Debt to Asset Ratio is the independent variable, and Company Profitability is the dependent variable. The results of the correlation analysis found a linear relationship between the variables. The results of the regression analysis found that there was a shallow level of influence. This study has several limitations on the number of samples, variables, and industrial sectors studied. In addition, other factors also need to be considered-some recommendations for further research. They expanded the study sector, examining other factors such as accounts receivable turnover and company size.

PENGARUH INDEPENDENSI, OBJEKTIVITAS, PENGALAMAN KERJA, KOMPETENSI, INTEGRITAS DAN SKEPTISME PROFESIONALTERHADAP KUALITAS AUDIT (STUDI DI INSPEKTORAT PROVINSI BENGKULU)

This study aims to find empirical evidence regarding the effect of independence, objectivity, work experience, competence, integrity and professional skepticism on audit quality at the Bengkulu Provincial Inspectorate. The type of research used in this research is quantitative research. The type of data used is primary data in the form of values or scores for the answers given by respondents to the questions in the questionnaire. The sampling technique used is the saturated sample/census method.
 Based on sampling through the saturated sample/census method, 46 samples of Bengkulu Province Inspectorate auditors were obtained. The data was processed through the multiple linear regression statistical test method using SPSS software version 21. The results of the study found that competence had a positive effect on audit quality. Meanwhile, independence, objectivity, work experience integrity and professional skepticism have no effect on audit quality.

Robust production forecast and uncertainty quantification for waterflooding reservoir using hybrid recurrent auto-encoder and long short-term memory neural network

History-matching-based production forecast and uncertainty quantification are essential to achieve reliable risk assessment for waterflooding reservoir in the community of petroleum engineering, however, the conventional model-based history matching procedure presents intensive computation-cost due to numerous high-fidelity reservoir simulations. The use of direct forecast approach, e.g., data-space inversion (DSI) and its variants, is urgent to achieve direct production forecast without explicitly performing history matching. This work presents a generic data-driven post-history production forecasting framework using a novel deep recurrent neural network. We construct a hybrid recurrent neural network proxy through combining recurrent autoencoder with long short-term memory neural network, e.g., referred to as RAE-LSTM. The proposed RAE-LSTM takes history prediction and post-history well controls as input, while the post-history production responses (oil and water production, water injection rate) as output. Training samples are constructed by simulating high-fidelity models parameterized with various post-history well-controls and geomodels. Once the deep recurrent neural network proxies are trained offline, the online post-history production forecast and uncertainty quantification can be efficiently achieved by input user-specific well control sequences and history measurement. The proposed proxy model is demonstrated on two examples with varying complexity, e.g., a synthetic 2D Gaussian model and a 3D channelized EGG model. The use of our proposed RAE-LSTM neural network can be regarded as a nonlinear alternative to the DSI-type of linear statistical interpolation method. The comparisons between DSI and RAE-LSTM proxy confirm that the application of our proposed data-driven prediction method can effectively obtain more robust predictions and thus support rapid and reliable decision-making during the process of real-time waterflooding production management and optimization.

PENGARUH PERUBAHAN LAHAN PERTANIAN MENJADI NON PERTANIAN TERHADAP ASPEK SOSIAL EKONOMI MASYARAKAT

The transformation that occurs in the peri-urban area will cause changes in the morphological peri-urban area and affect changes in the form of agricultural land use and have an impact on changes in the socio-economic conditions of the people in the area. The purpose of this study was to determine the influence of changes in agricultural land to non-agriculture on the socio-economic aspects of the community in Jati Agung. This research uses a deductive approach. The data collection method used primary data from questionnaires and interviews, the secondary data collected from Landsat 8 satellite image and BPS South Lampung Regency in 2013-2020. The method of analysis uses the predominant peri-urban zone classification with urban or predominantly urban characteristics divided into Urban Frame Zones and Urban-rural Frame Zones, which have a percentage of agricultural land use less than 50%. Statistical linear regression method is used to see the effect of the transformation of agricultural land use into non-agriculture on the socio-economic aspects of the peoples. The results of statistical tests show that there is a disproportionate effect with a large effect of 29.5% on the total population, 7.6% on population density, 8.6% on Livelihoods and 20.2% on income.

Pengaruh Anggaran Pendapatan Belanja Daerah Terhadap Program Pengentasan Kemiskinan Di Kabupaten Aceh Selatan

South Aceh Regency has 18 scattered sub-districts, and the distribution of the sub-district population is uneven so that it has an impact on differences in the population's economy between Tapak Tuan City and other sub-districts. It is inevitable that poverty will still hit this district, according to data from the Central Statistics Agency (BPS) the poverty rate for South Aceh Regency will reach 32.700 in 2022. To help the less fortunate, the government has made efforts to provide assistance sourced from the regional expenditure revenue budget.This research was made to find out and explain the extent of the influence of regional expenditure budgets on poverty alleviation in South Aceh district. This research was conducted from January to May 2023, using the Simple Linear Regression statistical data analysis method to make it easier for researchers to get the desired results. data brought by this researcher from the Central Statistics Agency (BPS) of South Aceh RegencyThe regression coefficient obtained is 4.468E-6 with a significant value of 0.259> 0.05 where it is shown that the coefficient is positive, so what is obtained is that there is a close relationship between the regional expenditure budget and poverty, where if the APBD budget has increased then there is also an increase in poverty. From the results of R square, it is found that 77.3% of this can be used to see the magnitude of the influence. From the calculated t value of 3.197%, which means it is in the receiving area of Ha. F value count 10.220

Alongwind and crosswind response of friction-pendulum base-isolated high-rise buildings

Base isolation technology is widely accepted as an effective strategy for the seismic design of buildings. Although the elastomeric isolator is still extensively adopted for the base-isolation system in practice, there is a trend to use the frictional pendulum bearing (FPB) due to its high vertical bearing capacity, stable performance and good recentering capability. In this paper, the dynamic response of base-isolated high-rise buildings with FPB having a velocity-dependent friction coefficient subjected to uncoupled alongwind and crosswind loads is studied. The response characteristics calculated from response history analysis (RHA) are analyzed. Meanwhile, two statistical linearization methods are utilized to estimate the standard deviation (STD) of the structural response and to obtain the equivalent parameters of the linearized system. The time-varying mean of the base displacement under alongwind load with a non-zero mean is also discussed by the linearization method. Finally, a parameter analysis of the isolation bearing is performed to investigate the effects of the radius and friction coefficient of the sliding plate on the wind-induced vibration. This study highlights the strong nonlinear response characteristics of base-isolated high-rise buildings with FPB and offers design guidelines under strong winds.

Approximate Kalman filtering by both M-robustified dynamic stochastic approximation and statistical linearization methods

The problem of designing a robustified Kalman filtering technique, insensitive to spiky observations, or outliers, contaminating the Gaussian observations has been presented in the paper. Firstly, a class of M-robustified dynamic stochastic approximation algorithms is derived by minimizing at each stage a specific time-varying M-robust performance index, that is, general for a family of algorithms to be considered. The gain matrix of a particular algorithm is calculated at each stage by minimizing an additional criterion of the approximate minimum variance type, with the aid of the statistical linearization method. By combining the proposed M-robust estimator with the one-stage optimal prediction, in the minimum mean-square error sense, a new statistically linearized M-robustified Kalman filtering technique has been derived. Two simple practical versions of the proposed M-robustified state estimator are derived by approximating the mean-square optimal statistical linearization coefficient with the fixed and the time-varying factors. The feasibility of the approaches has been analysed by the simulations, using a manoeuvring target radar tracking example, and the real data, related to an object video tracking using short-wave infrared camera.

Minute-Scale Models for the Diffuse Fraction of Global Solar Radiation Balanced between Accuracy and Accessibility

The separation models are tools used in solar engineering to estimate direct normal (DNI) and diffuse horizontal (DHI) solar irradiances from measurements of global solar irradiance (GHI). This paper proposes two empirical separation models that stand out owing to their simple mathematical formulation: a rational polynomial equation. Validation of the new models was carried out against data from 36 locations, covering the four major climatic zones. Five current top minute-scale separation models were considered references. The tests were performed on the final products of the estimation: DNI and DHI. The first model (M1) operates with eight predictors (evaluated from GHI post-processed measurements and clear-sky counterpart estimates) and constantly outperforms the already established models. The second model (M2) operates with three predictors based only on GHI measurements, which gives it a high degree of accessibility. Based on a statistical linear ranking method according to the models’ performance at every station, M1 leads the hierarchy, ranking first in both DNI and DHI estimation. The high accessibility of the M2 does not compromise accuracy; it is proving to be a real competitor in the race with the best-performing current models.

A novel regression method: Partial least distance square regression methodology

Partial Least Squares (PLS) is a multivariate linear statistical analysis method integrating principal component analysis (PCA), canonical correlation analysis (CCA), and multiple linear regression (MLR) analysis. It can effectively solve the problems of multiple correlation between variables and small sample size. However, PLS also has some imperfections, on the one hand, PLS extracts the latent variables based on the maximization of Pearson correlation coefficient of independent and dependent variables. Here, Pearson correlation coefficient usually cannot measure the nonlinear relationship between variables, so the latent variables cannot ensure the strongest interpretation. On the other hand, PLS applies MLR to the extracted latent variables, which cannot truly reflect the nonlinear relationship of data, so the regression function is usually under-fitting. The above two imperfect designs are the main reasons for the low regression accuracy and prediction performance of PLS for nonlinear data. According to the above problems, this paper proposes a Partial Least Distance Square (PLDS) regression method. PLDS reflects the original data information through distance variance in PCA, employs distance correlation coefficient to measure the correlation between independent and dependent variables in CCA, and performs quasilinear regression and model solution method to obtain the final regression equation in MLR. In order to verify the effectiveness of the proposed method, the UCI datasets and Chinese medicine datasets with dose-effect relationship was used to compare the new method with other classical regression methods. Finally, the experimental results show that PLSD has better prediction performance regardless of whether there is significant nonlinear relationship between variables. In addition, PLDS has high regression accuracy and low computation complexity for high-dimensional and small-sample data.

PENGARUH KEBIJAKAN DIVIDEN, KEPUTUSAN INVESTASI, DAN LABA BERSIH TERHADAP HARGA SAHAM PADA MASA PANDEMI DI PERUSAHAAN BURSA EFEK INDONESIA (BEI)

In manufacturing companies have a very important role because they are the basic ingredients needed by people on daily basis. Therefore, we need to know the dividend policy that investors get, the invesment decisions that investors can take, and how much net profit the company earned during the pandemic. The sample in this study consisted of 23 manufacturing companies with an observation period from 2020-2021. Sample selection using purposive sampling method. The analytical method used in this research is descriptive statistical and multiple linear regression analysis method. The data used is secondary data. The tool used to test the classic and hypothesis testing using Eviews 12. The results of this study indicate that the dividend policy,investment decisions, and net profit partially has a positive and significant effect on stock prices. Simultaneously, dividend policy, invesment decisions, and net profit have an effect on stock prices.

Oil Monitoring and Fault Pre-Warning of Wind Turbine Gearbox Based on Combined Predicting Method

Oil monitoring for wind turbine gearboxes can reflect wear and lubrication conditions, and better identify pits on the tooth surface, fatigue wear, and other early faults. However, oil monitoring with one or several single predicting models brings inaccuracy due to the intrinsic merits and demerits of the models. In this work, oil monitoring and fault pre-warning of wind turbine gearboxes were studied based on oil inspection data of three wind turbines that have been working continuously for 3.5 years. The Grey Model (GM) and the Double Exponential Smoothing (DES) were combined by a modified inverse-variance weighting method proposed in this work, which used relative errors to calculate weight coefficients, reducing the errors and improving the accuracy as a whole. The predicted data were compared with the measured data to verify the predicting accuracy. Subsequently, a statistical method and linear regression method were adopted to jointly develop a pre-warning threshold for the oil inspection data. Comparing the predicted data with the threshold, the results showed that one of the wind turbines was in a warning state. The prediction was validated by an endoscope inspection of the gearbox, which found that some parts were slightly worn.

Analisis Hubungan Nilai Tukar Nelayan Dengan Jenis Tangkapan Nelayan Di Desa Pengambengan, Kecamatan Negara, Kabupaten Jembrana, Bali

This research aims to determine the fishermen’s exchange rate (NTN) and how the catch composition could affect the income of purse sein fishermen in Pengambengan Village. The object of the research is purse sein fishermen in Pengambengan Village, sampling has carried out by using purposive technique, and data was collected using questionnaires and interviews. The method used in this research are the NTN calculation method and multiple linear regression statistical method with hypothesis test, T-tets, F-test, and the coefficient of determination (adjusted R2 Square). The results show in the harvest season, almost all of the fishermen experienced a surplus (NTN above 100), while in the famine season only fishermen with high profit-sharing system experienced a surplus and the other experienced a disadvantage. For both of the two seasons, the fishermen’s catch composition are consist of lemuru, tongkol and layang; base on the T-test results, lemuru catch affect significantly on fishermen’s income during the harvest season, and layang catch affect the income of fishermen in the famine season. somultaneously the catch composition, lemuru, tongkol and layang affect fishermen income compared only 1 type of fish catch, and seen from the Coefficient of Determination by 6,6 % in the harvest and by 7,5 % in the famine season. The fishermen’s income is also influenced by other variables which are not included. in the model.

FACTORS AFFECTING USER SATISFACTION ON e-FILING SYSTEM IN INDONESIA

One of the electronic tax systems used in Indonesia is e-Filing which results in an increase in the number of users. However, the high intensity of using the system does not guarantee that the system is successful and fully supports user needs. This study was conducted to determine the determinants of e-Filing user satisfaction by adopting several models of measuring system success formulated by Delone and Mclean. This research contributes to measuring and providing improvements to the entire tax information system in Indonesia. The study was conducted using a survey method (questionnaire) and purposive sampling on 562 lecturers of the State Polytechnic of Malang. Using the multiple linear regression statistical method and in accordance with the hypothesis in the study, the results showed that partially System Quality, Information Quality and Service Quality had a positive effect. and significant to User Satisfaction. In addition, simultaneously System Quality, Information Quality and Service Quality have a positive and significant effect on User Satisfaction.

Simple Regression Modeling on the Number of Fronds Increases with Age on Oil Palm Seedling’s Growth

The productivity of oil palm crops is a crucial factor in the current oil palm plantation industry, considering the prevalent issues and criticisms about the environmental impact of land clearing for oil palm plantations. Given that the productivity of oil palm crops is determined by their quality and growth rate, it is important to study the speed and quality of oil palm crop growth during the early stages, namely seedling growth, where the number of fronds can be measured. This research aims to analyse the number of seedling fronds growing during their 9-month growth period since being transferred from the pre-nursery to the main nursery plantation. The fronds growth observation results of 300 seedlings over nine months are evaluated using the distribution analysis each month, and the growth model in the form of a linear equation is developed using a statistical linear regression method. The correlation coefficients indicate a reasonably significant increase in the number of fronds as the age of the seedlings, with R values = 0.6728, R = 0.8346, and R = 0.9489 for the minimum, the maximum and average number of fronds, respectively. It is concluded that the growth of the number of oil palm fronds can be easily simulated using the developed regression model.

METHOD FOR CALCULATION OF DISPERSIONS OF DEPENDENT VARIABLES OF A STOCHASTIC MODEL OF QUASI-STATIONARY OPERATING MODES OF THE MAIN WATER PIPELINE

The subject of research in the article is a stochastic model of quasi-stationary modes of operation of water supply and distribution systems, which adequately describes the actual operating modes of the water supply system for a given time interval and can be used as a basic model for setting and solving problems of optimal stochastic control of the development and operation of supply and distribution systems. water. The goal of the work is to develop a method for calculating estimates of the dispersions of dependent variables depending on the given values of mathematical expectations and dispersions of independent variables for a stochastic model of quasi-stationary modes of operation of the main water conduit as a subsystem of the water supply and distribution system. To achieve this goal, it is necessary to solve the following tasks: to build a deterministic equivalent of a stochastic model of quasi-stationary modes of operation of the main water conduit; calculate estimates of mathematical expectations of dependent variables; calculate estimates of variances of dependent variables. To calculate estimates of the variances of dependent variables depending on the variances of independent variables, we will use the method of statistical linearization. To obtain estimates of mathematical expectations of dependent variables, the deterministic equivalent of the stochastic model of quasi-stationary modes of operation of the main water conduit is solved by the modified Newton method. The following results are obtained: a method for calculating estimates of the dispersions of dependent variables for a stochastic model of quasi-stationary modes of operation of the main water conduit. Conclusions: the paper proposes an approximate method for calculating the statistical properties of dependent variables depending on the statistical properties of the parameters and independent variables of the stochastic model of quasi-stationary modes of operation of the main water conduit. The proposed method is based on the construction of a deterministic equivalent of a stochastic model of quasi-stationary modes of operation of the main water conduit and its use for calculating estimates of variances of dependent variables depending on the given values of mathematical expectations and variances of independent variables. Compared with the simulation method, the proposed approximate method does not require significant time and computational resources. The use of the proposed method was demonstrated by an example.