Exponential Method Research Articles

ETHEREUM CRYPTOCURRENCY PRICE MOVEMENT PREDICTION SYSTEM USING TRIPLE EXPONENTIAL SMOOTHING METHOD

An innovation that was sparked is an alternative currency to replace conventional currency, namely digital currency that is secured using a cryptographic method called Cryptocurrency. However, cryptocurrency prices cannot be controlled, causing massive fluctuations. Cryptocurrency price changes are very stable due to several factors such as speculation from users and the nature of the follow-up from new to one of the causes. The cause of this bandwagon is due to extreme price increases in a short time, even within a day the price of Crypto can experience a difference of millions of rupiah for each increase and decrease. To answer this question, we need a software that can predict the Rupiah exchange rate. By using the Triple Exponential Smoothing prediction method. In implementing Triple Exponential Smoothing, historical data is needed which will later be processed to produce prediction results, for that we need parameters that can be used as historical data counters, in this study used parameters 0.40 as parameters Xt and S't and 0.60 as Beta parameters. In the process, starting from calculating the first to third smoothing, ensuring Constants, Slopes, and Parabolics, to completing the process by producing Forecasting, the results of the measurement of the margin error level with a margin of error of 0.94638% using data for the final 2021 period, which is between November - December on the Triple Exponential implementation simulation and on the implementation into the system that has been developed is 3.7249% using data from May 2022 to June 2022.

On the Nonlinear Mathematical Model Representing the Coriolis Effect

In this study, the traveling wave solutions of a nonlinear partial differential equation (NPDE) called as Geophysics Korteweg-de Vries (GpKdV) equation are obtained using the modified exponential function method (MEFM). Coriolis effect is stated with the help of this model used in geophysics. The nonlinear model has a Coriolis coefficient representing this effect.

Coniochaeta massiliensis sp. nov. Isolated from a Clinical Sampl28.

The genus Coniochaeta belongs to the class Ascomycota and the family Coniochaetaceae. Some of the Coniochaeta species are plant and animal pathogens, while others are known to be primarily involved in human diseases. In the last few decades, case reports of human infections with Coniochaeta have increased, mainly in immunocompromised hosts. We have described and characterised a new species in the genus Coniochaeta, here named Coniochaeta massiliensis (PMML0158), which was isolated from a clinical sample. Species identification and thorough description were based on apposite and reliable phylogenetic and phenotypic approaches. The phylogenetic methods included multilocus phylogenetic analyses of four genomic regions: ITS (rRNA Internal Transcribed Spacers 1 and 2), TEF-1α (Translation Elongation Factor-1alpha), B-tub2 (β-tubulin2), and D1/D2 domains (28S large subunit rRNA). The phenotypic characterisation consisted, first, of a physiological analysis using both EDX (energy-dispersive X-ray spectroscopy) and BiologTM advanced phenotypic technology for fixing the chemical mapping and carbon-source oxidation/assimilation profiles. Afterwards, morphological characteristics were highlighted by optical microscopy and scanning electron microscopy. The in vitro antifungal susceptibility profile was characterised using the E-testTM exponential gradient method. The molecular analysis revealed the genetic distance between the novel species Coniochaeta massiliensis (PMML0158) and other known taxa, and the phenotypic analysis confirmed its unique chemical and physiological profile when compared with all other species of this genus.

Efficient seismic fragility analysis of structures from dynamic reliability perspective

Seismic fragility analysis of structures quantitatively describes the relationship between the failure probabilities of structures and ground motion Intensity Measures (IMs). Generally, two steps are involved: (1). calculating the failure probabilities of the structure under consideration at a set of IM levels; (2). regressing the IM levels and the corresponding failure probabilities to obtain a bunch of fragility curves. In this paper, a new method is proposed for seismic fragility analysis of structures from a dynamic reliability perspective, where efficiency and accuracy are emphasized. First, the dynamic reliability of structures under fully non-stationary ground motions is presented, where the Fractional Exponential Moments-based Maximum Entropy Method (FEM-MEM) is applied to derive the extreme value distribution with high efficiency. In this method, only a total of 89 samples of fully non-stationary ground motions generated by the spectral representation method and consistent with the design response spectrum that are sufficient in the FEM-MEM for efficient dynamic reliability computations are required. Then, a four-parameter distribution model, which exhibits high flexibility, is used to recover the fragility curves. A two-step strategy is developed for parameter estimation based on four failure probabilities at four different IM levels. In addition, a strategy for selecting a small number of IM levels for all damage states is also suggested, which improves the computational efficiency. Two numerical examples, including a seven-story nonlinear shear frame structure and a five-story three-span frame structure designed according to Chinese codes, are investigated to verify the effectiveness of the proposed method, where the results obtained from the traditional lognormal distribution are also compared.

DECISION SUPPORT SYSTEM FOR HYDROPONIC VEGETABLE SEED SELECTION USING EXPONENTIAL COMPARISON METHOD

The issue of food security is not only the task of farmers, therefore starting to participate in growing vegetables at home through hydroponic techniques can be a solution. Hydroponics is one solution for urban farming or farming activities independently in urban areas in Indonesia. In order to get an abundant harvest on limited land, it requires quality seeds. Good vegetable seeds hold the key to determining a good harvest too. So, you should not carelessly buy vegetable seeds to grow vegetables hydroponically. But the problem is, with so many vegetable seed products for hydroponics on the market, it makes someone confused to choose the right product that suits their needs. The main purpose of this research is to develop a decision support system for selecting hydroponic vegetable seeds with a website-based Exponential Comparison Method to facilitate decision makers in determining the right seeds and according to their needs. The Exponential Comparison method can perform a priority order of decision alternatives on existing criteria and can distinguish the value of each alternative in contrast. The decision support system developed produces calculations using the valid Exponential Comparison Method because the results are in accordance with manual calculations. In addition, based on the black-box testing technique, it shows that the system built has been running well.

Application of modified exponential rational function method to Jaulent–Miodek system leading to exact classical solutions

The Jaulent–Miodek (JM) system is investigated analytically in this study. The JM equation comes with energy-dependent Schrödinger potential which is used in fluid dynamics, optics, condensed matter physics and engineering systems. As a result, it is critical to investigate this dynamical problem from a mathematical point of view. The generalized exponential rational function method is applied to extract the exact solutions of JM system. These exact traveling wave solutions are successfully extracted in the form of trigonometric, hyperbolic, rational, and exponential functions. The suitable choices of parameters are granted to draw the plots of some solutions. The physical behaviors of these solutions are shown physically, which are helpful to understand the physical phenomena of these dynamical model which are arisen in the mathematical physics.

Wave Solution Analysis of a Nonlinear Mathematical Model on Fluid Mechanics

This study obtains some wave solutions of the B-type Kadomtsev Petviashvili equation by applying the modified exponential function method (MEFM). Due to the nature of the MEFM, two different cases are presented here, which we analyzed to obtain more of the solutions in this structure. More wave solutions can be obtained by analyzing different situations. When the resulting solutions are analyzed, hyperbolic, trigonometric, and rational functions are observed. It has been checked whether the solution functions found with Wolfram Mathematica software provide the B type Kadomtsev Petviashvili equation and graphs simulating the wave solution behavior with the determined appropriate parameters are presented.

Hybrid uncertainty propagation and reliability analysis using direct probability integral method and exponential convex model

Uncertainty propagation and reliability evaluation, being the crucial parts of engineering system analysis, play vital roles in safety assessment. How to reasonably consider the complex multisource uncertainty behavior in both static and dynamic systems is paramount to ensuring their safe operation. However, there is a significant lack of research on aleatory and epistemic uncertainties for both static and dynamic systems. To this end, a new hybrid exponential model is proposed by combining probabilistic and non-probabilistic exponential models, which aims to accurately measure the uncertainty propagation and reliability evaluation problem with aleatory and epistemic uncertainties for static and dynamic systems. The proposed hybrid exponential model consists of nested double optimization loops. The outer loop performs a probabilistic analysis based on the direct probability integral method, and the inner loop performs a non-probabilistic computation. Then, a new hybrid exponential probability integral method is developed to effectively perform uncertainty propagation and reliability analysis. Finally, four examples, including two static and two dynamic examples with complex performance functions, are tested. The results indicate that the proposed hybrid exponential model offers a universal tool for uncertainty quantification in static and dynamic systems. Moreover, the hybrid exponential probability integral method can accurately and efficiently obtain the upper and lower bounds of the probability density function and cumulative distribution function.

Development of look-ahead NURBS interpolation based on the exponential function

Aiming at the problem of large number of points and complex calculation of NURBS pre-interpolation, this paper puts forward a look-ahead interpolation with offline feedrate optimization. The NURBS interpolator is divided into two stages: pre-interpolation and real-time interpolation. The pre-interpolation preprocesses the curve segment by segment according to the curvature characteristics, at the same time the exponential function method is adopted during the pre-interpolation in the look-ahead module. This method makes the step increment of interpolation parameters change exponentially in the area with gentle curvature, and greatly reduces the number of pre-interpolation points, which reduces the amount of calculation and improves the real-time performance. The real-time interpolation stage adopts the bidirectional adaptive acceleration and deceleration control method to realize speed smoothing without needing to calculate the deceleration point. The simulation results show that the real-time performance of the algorithm is greatly improved.

Multi-peak soliton solutions of the generalized breaking soliton equation

In this article, we apply the generalized exponential rational function method to find soliton solutions of generalized (3+1)-dimensional breaking soliton equation, which describes two-dimensional interchange of Riemann wave disseminating alongside y-axis with a long wave disseminating alongside x-axis. As a result, we obtain many soliton solutions to the equation by choosing appropriate parameters. We demonstrate a variety of travelling waves using three-dimensional, two-dimensional and contour plots. We observe that solutions involving parameters can drastically influence the behaviour of solitary waves. Such solutions are applicable to enrich the dynamical study of nonlinear waves in fluid dynamics and other fields of research.

A study on the solutions of (1+1)-dimensional Mikhailov-Novikov-Wang equation

The basic principle of this study is to obtain various solutions to the (1+1) dimensional Mikhailov-Novikov-Wang integrable equation (MNWIE). For this purpose, the generalized exponential rational function method (GERFM) is applied to this equation. Thus, several trigonometric functions, hyperbolic functions, and dark soliton solutions to the studied equation are acquired. In this way, some new solutions to the equation that have not been presented before have been obtained. In addition, 2D and 3D graphics of the acquired solutions are drawn for specific values. The obtained results and the graphic drawings of the results have been provided by using Wolfram Mathematica 12.

Kinerja Algoritma Yamamoto’s Recursive Code dan Algoritma Fixed Length Binary Encoding pada Kompresi File PDF

The use of files in digital form is currently growing and requires media to store them. The more files that store, the more storage space need. This encourages the development of file reduction techniques or data compression techniques with the aim of reducing the required storage space. The compression technique has several algorithms that can be used to compress files such as Yamamoto's recursive code algorithm and Fixed Length Binary Encoding (FLBE). These algorithms have different performance to produce quality compressed results, so they need to be compared. This study describes the analysis and comparison of the performance of the two algorithms based on the exponential method as measured by the quality of the compressed pdf file. The exponential comparison method is one of the methods of the Decision Support System (DSS) to determine the priority order of decision alternatives with multiple criteria. Compression quality parameters that are measured as an alternative comparison are the value of the ratio of compression, compression ratio, space saving. Based on the results of the comparison with Exponential Comparison Method (MPE), it was found that the fixed length binary encoding algorithm has a better performance with a value of 2.55% compared to the Yamomoto's recursive code algorithm with a smaller value of 2.22%.

Penerapan Metode Perbandingan Eksponensial (MPE) Dalam Menentukan Topik Skripsi, Dosen Pembimbing Beserta Dosen Pembanding Studi Kasus Fakultas Ilmu Komputer Universitas Methodist Indonesia

The research that the author made discusses the application of the exponential comparison method (MPE) in determining thesis topics, supervisors and comparative lecturers of case studies at the Faculty of Computer Science, Indonesian Methodist University which aims to produce decisions in the selection of thesis topics, supervisors and comparison lecturers according to the criteria in Indonesian Methodist University. A decision support system (SPK) is needed that can find the student title value from each criterion that has been determined by the Indonesian Methodist University for the decision-making process. Applying the Exponential Comparison Method (MPE) using the criteria that have been determined by the campus, namely being registered as active students, having completed a minimum of 100 credits, students conducting research and compiling thesis manuscripts. The decision support system for selecting topic titles, supervisors and comparison lecturers made by the author uses the PHP programming language, and uses a MySQL database that is run on the Windows operating system

Modified exponential time series model with prediction of total COVID-19 cases in Belgium, Czech Republic, Poland and Switzerland

Abstract The coronavirus (COVID-19) pandemic affected every country worldwide. In particular, outbreaks in Belgium, the Czech Republic, Poland and Switzerland entered the second wave and was exponentially increasing between July and November, 2020. The aims of the study are: to estimate the compound growth rate, to develop a modified exponential time-series model compared with the hyperbolic time-series model, and to estimate the optimal parameters for the models based on the exponential least-squares, three selected points, partial-sums methods, and the hyperbolic least-squares for the daily COVID-19 cases in Belgium, the Czech Republic, Poland and Switzerland. The speed and spreading power of COVID-19 infections were obtained by using derivative and root-mean-squared methods, respectively. The results show that the exponential least-squares method was the most suitable for the parameter estimation. The compound growth rate of COVID-19 infection was the highest in Switzerland, and the speed and spreading power of COVID-19 infection were the highest in Poland between July and November, 2020.

ANALISIS PERBANDINGAN METODE EXPONENTIAL APPROACH DAN METODE IMPROVED ZERO POINT UNTUK MEMINIMUMKAN BIAYA PENDISTRIBUSIAN

The purpose of this study is to do a comparative of the minimum cost of distributing mountea drinks using the exponential approach and the improved zero point method. The exponential approach method is a direct method where the allocation in this method depends on the number of zeros that appear in the transportation table. In the case of an unbalanced transportation problem, a dummy line (column) will appear where the cost on the line (column) is zero, which will greatly affect the optimum results of the given exponential approach method. The improved zero point method is an improved method from the zero point method, which is very useful for solving all types of transportation problems. This method provides an optimal solution without the help of other modified methods. Based on the results of the research, it was shown that the distribution cost of mountea drinks from the wholesale center in the Lunyuk sub-district using an exponential approach and an improved zero point obtained a cost of 10,392,276 Rupiah before the optimization, while the while the comparative distribution cost of the mountea drinks from the wholesale center in the Lunyuk sub-district after the optimization using an exponential approach and an improved zero point obtained a cost same of 8.552.560 Rupiah.

High-order bound-preserving discontinuous Galerkin methods for multicomponent chemically reacting flows

In this paper, we design high-order bound-preserving discontinuous Galerkin (DG) methods for multicomponent chemically reacting flows. In this problem, the density and pressure are positive and the mass fractions are between 0 and 1. There are three main difficulties. First of all, it is not easy to construct high-order positivity-preserving schemes for convection-diffusion equations. In this paper, we design a special penalty term to the diffusion term and construct the positivity-preserving flux for the system. The proposed idea is locally conservative, high-order accurate and easy to implement. Secondly, the positivity-preserving technique cannot preserve the upper bound 1 of the mass fractions. To bridge this gap, we apply the positivity-preserving technique to each mass fraction and develop consistent numerical fluxes in the system and conservative time integrations to preserve the summation of the mass fractions to be 1. Therefore, each mass fraction would be between 0 and 1. Finally, most previous bound-preserving DG methods are based on Euler forward time discretization. However, due to the rapid reaction rates, the target system may contain stiff sources, leading to restricted time step sizes. To fix this and preserve conservative property, we apply the conservative modified exponential Runge-Kutta method. The method is third-order accurate and keeps the summation of the mass fractions to be 1. Numerical experiments will be given to demonstrate the good performance of the proposed schemes.

Estimation of transpiration coefficient and aboveground biomass in maize using time-series UAV multispectral imagery

Estimating spatial variation in crop transpiration coefficients (CTc) and aboveground biomass (AGB) rapidly and accurately by remote sensing can facilitate precision irrigation management in semiarid regions. This study developed and assessed a novel machine learning (ML) method for estimating CTc and AGB using time-series unmanned aerial vehicle (UAV)-based multispectral vegetation indices (VIs) of maize under several irrigation treatments at the field scale. Four ML regression methods: multiple linear regression (MLR), support vector regression (SVR), random forest regression (RFR), and adaptive boosting regression (ABR), were used to address the complex relationship between CTc and VIs. AGB was then estimated using exponential, logistic, sigmoid, and linear equations because of their clear mathematical formulations based on the optimal CTc estimation model. The UAV VIs-derived CTc using the RFR estimation model yielded the highest accuracy (R2 = 0.91, RMSE = 0.0526, and nRMSE = 9.07%). The normalized difference red-edge index, transformed chlorophyll absorption in reflectance index, and simple ratio contributed significantly to the RFR-based CTc model. The accuracy of AGB estimation using nonlinear methods was higher than that using the linear method. The exponential method yielded the highest accuracy (R2 = 0.76, RMSE = 282.8 g m−2, and nRMSE = 39.24%) in both the 2018 and 2019 growing seasons. The study confirms that AGB estimation models based on cumulative CTc performed well under several irrigation treatments using high-resolution time-series UAV multispectral VIs and can support irrigation management with high spatial precision at a field scale.

Equilibrium point, exponential stability and synchronization of numerical fractional-order shunting inhibitory cellular neural networks with piecewise feature

In recent years, exponential Euler difference methods for first-order semi-linear differential equations have been developed rapidly, and various exponential Euler difference methods have become a very important research topic. For fractional-order shunting inhibitory cellular neural networks with time lags, this article first establishes a new difference method named Mittag-Leffler Euler difference, which includes exponential Euler difference. Second, the existence of unique global bounded solution and equilibrium point, exponential stability and synchronization of the derived difference model are investigated. Compared with the classical fractional-order Euler difference method, the Mittag-Leffler discrete shunting inhibitory cellular neural networks can better describe and maintain the dynamic properties of the corresponding continuous-time models. More importantly, it opens up a new way to study discrete-time fractional-order systems and establishes a set of theory and methods to study Mittag-Leffler discrete neural networks.

Optical solitons to the Ginzburg–Landau equation including the parabolic nonlinearity

The major goal of the present paper is to construct optical solitons of the Ginzburg–Landau equation including the parabolic nonlinearity. Such an ultimate goal is formally achieved with the aid of symbolic computation, a complex transformation, and Kudryashov and exponential methods. Several numerical simulations are given to explore the influence of the coefficients of nonlinear terms on the dynamical features of the obtained optical solitons. To the best of the authors’ knowledge, the results reported in the current study, classified as bright and kink solitons, have a significant role in completing studies on the Ginzburg–Landau equation including the parabolic nonlinearity.

RETRACTED: On soliton solutions of a modified nonlinear Schrödinger’s equation of third-order governing in optical fibers

Recently, the development of novel methods for finding solutions to partial differential equations has made great progress in various fields of science. These equations are an important tool in describing many phenomena that occur around us. The research work aims to study a third-order nonlinear Schrödinger’s equation using the modified generalized exponential rational function method, and the extended sinh-Gordon equation expansion method. The common idea between the two methods is that it is first necessary to reduce the equation with partial derivatives to a form of the equation with ordinary derivatives using a new wave definition. Moreover, the retrieved solutions are obtained in a closed form of elementary functions which are important in practical applications. We successfully construct some soliton, singular soliton and singular periodic wave solutions to the nonlinear complex model. Further, numerical simulations are also included via several figures. A significant advantage of both techniques is the ability to introduce a wide range of types of analytical solutions in terms of well-known elementary functions. It is obtained that these methods are also applicable in solving other equations in nonlinear science.