PEMODELAN HARGA EMAS DUNIA MENGGUNAKAN METODE NONPARAMETRIK POLINOMIAL LOKAL DILENGKAPI GUI R

Investing in gold is a flexible choice because it can be sold at any time and used as an emergency fund. Investors should have the knowledge to predict data from time to time to achieve investment goals. One of the statistical methods for time series data modeling is ARIMA. The ARIMA model is strict with the assumptions that the data must be stationary, the residuals must be normally distributed, independent, and with constant variance, so an alternative model is proposed, namely nonparametric regression model, which has no modeling assumptions requirement. In this study, the daily world gold price data will be modeled using a local polynomial nonparametric model as an alternative because the assumptions in the ARIMA are not fulfilled. The data is divided into 2 parts, namely in sample data from January 2, 2020 to November 30, 2020 to form a model and out sample data from December 1, 2020 to December 31, 2020 used for evauation of model performance based on MAPE values. The chosen best model is the local polynomial model with Gaussian kernel function of degree 5, bandwidth of 373, and local point of 1744 with an MSE value of 482.6420. The local polynomial model out sample data MAPE value is 0.61%, indicating that the model has excellent forecasting capability. In this study, Graphical User Interface (GUI) using R software with the help of shiny package is also built, making data analyzing easier and generating more interactive display output.

Evaluating Fishing Capacity Based on DEA and Regression Analysis of China’s Offshore Fishery

The analysis of offshore fishing capacity is of great significance and practical value to the sustainable utilization and conservation of marine fishery resources. Based on the 2004–2020 China Fishery Statistical Yearbook, data envelopment analysis (DEA) was applied for measuring fishing capacity using a number of fishing vessels, total power, total tonnage, and the number of professional fishermen as the input measures and the annual catch as the output measure. Capacity utilization had a calculated range from 80.7 to 100%, and its average is 93.5%. In the first four years of 2003–2007, the excess investment rate of fishing vessels, total tonnage, total power, and fishermen was low (<5%). There was a consistent sharp upward trend in 2007, a gradual downward trend from 2007 to 2015, and an upward trend after reaching a low point in 2015, with the highest gross tonnage of fishing vessels reaching 25.5%. Four regression models that incorporate machine learning algorithms are used, including Lasso, Ridge, KNN, and Polynomial Features. The goodness of fit for the four models was used as the evaluation index, and the offshore annual catch based on the evaluation index was proposed. The forecasting annual catch of the polynomial model can reach 0.98. Furthermore, a comparative simulation of the DEA incorporating the polynomial model was carried out. The results show that DEA can evaluate input factors under the conditions of a given range, and the polynomial model has more advantages in forecasting annual catches. Furthermore, the combined application of DEA and polynomial model was used to analyze and discuss the management policies of China’s offshore fishery, which can provide help and reference for future management.

КОРПОРАТИВНІ ОБЛІГАЦІЇ ЯК ДЖЕРЕЛО РОЗВИТКУ ФІНАНСОВОГО ПОТЕНЦІАЛУ СУБ’ЄКТІВ ГОСПОДАРЮВАННЯ

The success of business entities depends on the ability to attract the necessary amount of financial resources to carry out activities. One of the most important issues in raising capital through the issuance of corporate bonds is to identify the factors and trends that affect this process in the context of developing the financial potential of economic entities. The aim of the research is to analyze the current state of the issue activity of business entities and determine the impact of the issue of corporate bonds on the capital formation of business entities. The subject of the research is the formation of capital through the issuance of bonds in the context of the development of the financial potential of economic entities. The methods of the research: generalization, comparison, trend analysis, trend models. The statement of basic materials. The article highlights the features of corporate bonds as an additional source of development of the financial potential of economic entities. The state and dynamics of issue activity of business entities on bond issue and activity on the secondary market of corporate bonds are analyzed. A nonlinear regression model has been formed, which reflects the dynamics of emission activity of economic entities. A polynomial model of capital dependence on bond issues of economic entities has been built. The practical significance of the research lies in the possibility of applying the built models in the process of forming a strategy of financial regulation of the development of economic entities. Conclusions and perspectives of further research. Corporate bonds are a potential source of financing for the development of economic entities. Trend analysis of the issue activity of enterprises on the issue of corporate bonds indicates the underdevelopment of this segment of the stock market. In the process of studying the financial potential of the development of economic entities should take into account the dependence of the formed capital and emission activity, activity in the secondary market of bonds of economic entities. The constructed models of nonlinear regression of the dynamics of bond issues and the polynomial model of the dependence of capital on bond issues of economic entities will increase the objectivity of forecasting.

Optimal Control of a 5-Link Biped Using Quadratic Polynomial Model of Two-Point Boundary Value Problem

To walk over constrained environments, bipedal robots must meet concise control objectives of speed and foot placement. The decisions made at the current step need to factor in their effects over a time horizon. Such step-to-step control is formulated as a two-point boundary value problem (2-BVP). As the dimensionality of the biped increases, it becomes increasingly difficult to solve this 2-BVP in real-time. The common method to use a simple linearized model for real-time planning followed by mapping on the high dimensional model cannot capture the nonlinearities and leads to potentially poor performance for fast walking speeds. In this paper, we present a framework for real-time control based on using partial feedback linearization (PFL) for model reduction, followed by a data-driven approach to find a quadratic polynomial model for the 2-BVP. This simple step-to-step model along with constraints is then used to formulate and solve a quadratically constrained quadratic program to generate real-time control commands. We demonstrate the efficacy of the approach in simulation on a 5-link biped following a reference velocity profile and on a terrain with ditches. A video is here: https://youtu.be/-UL-wkv4XF8.

Response surface design for removal of Cr(VI) by hydrogel-supported sulfidated nano zero-valent iron (S-nZVI@H)

In this study, a new sulfidated nanoscale zero valent iron (S-nZVI) supported on hydrogel (S-nZVI@H) was successfully synthesized for the removal of Cr(VI) from groundwater. The surface morphology, dispersion phenomenon and functional groups of novel S-nZVI@H were characterized by scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). Box-Behnken design (BBD) optimization technology based on response surface methodology (RSM) is applied to demonstrate the influence of the interaction of S-nZVI@H dose, initial Cr(VI) concentration, contact time, and initial pH with the Cr(VI) removal efficiency. The AVOVA results (F = 118.73, P &lt; 0.0001, R2 = 0.9916) show that the quadratic polynomial model is significant enough to reflect the close relationship between the experimental and predicted values. The predicted optimum removal conditions are determined to be as follows: S-nZVI@H dose 9.46 g/L, initial Cr(VI) concentration 30 mg/L, contact time 40.7 min and initial pH 5.27, and the S-nZVI@H dose is the key factor affecting the removal of Cr(VI). The predicted value (99.76%) of Cr (VI) removal efficiency is in good agreement with the experimental value (97.75%), which verifies the validity of the quadratic polynomial model. This demonstrates that RSM with appropriate BBD can be considerably utilized to optimize the design of experiments for removal of Cr(VI).

Optimizing the Sodium Hydroxide Conversion Using Regression Analysis in CSTR

The current study deals with the maximization of NaOH conversion using step-wise regression analysis in a CSTR. The dependence of temperature, volume, agitation rate, and feed rate on reactor performance is examined as well as interaction outcome of the operating parameters. The concentration of the reactants was fixed at 0.1 M. The steady state conversion with respect to NaOH is analyzed to find the process performance. Step-wise regression analysis is used to remove an insignificant factors. The agitation rate (X2) and feed rate (X3) proved to have an insignificant influence on the reaction conversion at a significant level (α) of 5%. Consequently, the temperature (X1) and reaction volume (X4) were found to have significant effect on the reaction conversion using step-wise regression. The temperature and volume dependence on steady state NaOH conversion were described by a polynomial model of 2nd and 3rd order. A maximal steady state conversion equal to 63.15% was obtained. No improvement was found in reaction conversion with 3rd order polynomial, so the second order polynomial is considered as the optimum reaction conversion modal. It may be recommended that 2nd order regression polynomial model adequately represents the experimental data very well.