A computational scheme to estimate the Leontief model matrix coefficients according to input-output table data for the southern regions of the Tyumen Oblast

2021 ◽  
Vol 19 (12) ◽  
pp. 2360-2383
Author(s):  
Denis A. GOVORKOV ◽  
Viktor P. NOVIKOV ◽  
Il'ya G. SOLOV'EV ◽  
Vladimir R. TSIBUL'SKII
Keyword(s):  
Least Squares Method ◽  
Estimation Algorithm ◽  
Balance Model ◽  
Input Output ◽  
Output Data ◽  
Tyumen Oblast ◽  
Estimation Algorithms ◽  
Additional Information ◽  
Output Matrix ◽  
Reference Input

Subject. This article deals with the control and management aspects of regional development on the basis of Leontief’s balance model. Objectives. The article aims to develop schemes for stable estimation of aggregate parameters of region balance models based on a shortened sample of input-output statistical data and rules for their subsequent regularization. Methods. For the study, we used multiple forms of regional economic balance model transformation based on the aggregation of data of the selected regional subsystems. Results. The primary estimates of aggregate input-output matrix for the southern regions of the Tyumen Oblast were obtained from the statistical input-output data for 2014–2018. To comply with the productivity conditions, additional information was introduced into the estimation algorithm reflecting the balance dependence for the reference input-output matrix for the Russian Federation and for the southern regions of the Tyumen Oblast in retrospective (2004–2013). Conclusions. The result of regularization of aggregate input-output matrix for the southern regions of the Tyumen Oblast obtained from the statistical input-output data on the basis of the least squares method indicates that the backward estimation technique cannot act as a basic tool for the primary construction of balance models of regional economies. However, backward estimation algorithms with subsequent regularization are effective in correcting the reference input-output matrix using actual data of the region’s socio-economic development.

scholarly journals Method of value chain mapping with international input–output data: application to the agricultural value chain in three Greater Mekong Subregion countries

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Ikuo Kuroiwa
Keyword(s):  
Value Chain ◽  
Value Added ◽  
Input Output ◽  
Output Data ◽  
Primary Input ◽  
Goods And Services ◽  
Unit Structure ◽  
Data Application ◽  
Final Output ◽  
Greater Mekong Subregion

AbstractExtending the technique of unit structure analysis, which was originally developed by Ozaki (J Econ 73(5):720–748, 1980), this study introduces a method of value chain mapping that uses international input–output data and reveals both the upstream and downstream transactions of goods and services, as well as primary input (value added) and final output (final demand) transactions, which emerge along the entire value chain. This method is then applied to the agricultural value chain of three Greater Mekong Subregion countries: Thailand, Vietnam, and Cambodia. The results show that the agricultural value chain has been increasingly internationalized, although there is still room to benefit from participating in global value chains, especially in a country such as Cambodia. Although there are some constraints regarding the methodology and data, the method proves useful in tracing the entire value chain.

scholarly journals AOIO: Application Oriented I/O Optimization for Buffer Management

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 573
Author(s):  
Xiaochang Li ◽  
Zhengjun Zhai ◽  
Xin Ye
Keyword(s):  
System Performance ◽  
Simulation Experiment ◽  
Buffer Management ◽  
Input Output ◽  
Output Data ◽  
Program Counter ◽  
Efficient Management ◽  
Management Scheme ◽  
Buffer Cache ◽  
Management Schemes

Emerging scale-out I/O intensive applications are broadly used now, which process a large amount of data in buffer/cache for reorganization or analysis and their performances are greatly affected by the speed of the I/O system. Efficient management scheme of the limited kernel buffer plays a key role in improving I/O system performance, such as caching hinted data for reuse in future, prefetching hinted data, and expelling data not to be accessed again from a buffer, which are called proactive mechanisms in buffer management. However, most of the existing buffer management schemes cannot identify data reference regularities (i.e., sequential or looping patterns) that can benefit proactive mechanisms, and they also cannot perform in the application level for managing specified applications. In this paper, we present an A pplication Oriented I/O Optimization (AOIO) technique automatically benefiting the kernel buffer/cache by exploring the I/O regularities of applications based on program counter technique. In our design, the input/output data and the looping pattern are in strict symmetry. According to AOIO, each application can provide more appropriate predictions to operating system which achieve significantly better accuracy than other buffer management schemes. The trace-driven simulation experiment results show that the hit ratios are improved by an average of 25.9% and the execution times are reduced by as much as 20.2% compared to other schemes for the workloads we used.

An Energy Efficient Estimation Algorithm for Wireless Sensor Network

2011 ◽  
Vol 216 ◽  
pp. 176-180
Author(s):  
Yong Ding ◽  
Yue Mei Su
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Estimation Algorithm ◽  
Efficient Estimation ◽  
Wireless Sensor ◽  
Estimation Algorithms ◽  
Current Energy

Wireless Sensor Networks functionality is closely related to network lifetime which depends on the energy consumption, so require energy- efficient protocols to improve the network lifetime. According to the analysis and summary of the current energy efficient estimation algorithms in wireless sensor network An energy-efficient algorithm is proposed,. Then this optimization algorithm proposed in the paper is adopted to improve the traditional diffusion routing protocol. Simulation results show that this algorithm is to effectively balance the network energy consumption, improve the network life-cycle and ensure the communication quality.

A Modified Algorithm for the Least Squares Identification

1983 ◽  
Vol 105 (1) ◽  
pp. 50-52
Author(s):  
C. Batur
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Mechanical Systems ◽  
Model Structure ◽  
Input Output ◽  
Unknown Parameters ◽  
Estimation Errors ◽  
Usual Practice ◽  
Unknown Disturbances ◽  
Modified Algorithm

To identify the dynamics of mechanical systems, the usual practice is to assume a certain model structure and try to estimate the unknown parameters of this model on the basis of input output observations. For mechanical systems operating under noisy industrial conditions, the number of unknowns of the problem exceeds the number of equations available. It is then inevitable that certain assumptions must be made on the unknown disturbances. This paper assumes that the only reliable feature of the disturbance is its independence of input. This yields a set of assumptions in excess of the minimal requirements and an endeavor has been made to exploit this excess to minimize the parameter estimation errors. Th resulting algorithm is similar to that of the Two Stage Least Squares method [1].

USING AN IMPROVED BEE MEMORY DIFFERENTIAL EVOLUTION ALGORITHM FOR PARAMETER ESTIMATION TO SIMULATE BIOCHEMICAL PATHWAYS

2014 ◽  
Vol 22 (01) ◽  
pp. 101-121 ◽  
Author(s):  
CHUII KHIM CHONG ◽  
MOHD SABERI MOHAMAD ◽  
SAFAAI DERIS ◽  
MOHD SHAHIR SHAMSIR ◽  
LIAN EN CHAI ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Estimation Algorithm ◽  
Convergence Time ◽  
Unknown Parameters ◽  
Estimation Algorithms ◽  
Bee Colony ◽  
De Algorithm ◽  
Cell Cycle Pathway ◽  
Parameter Values

When analyzing a metabolic pathway in a mathematical model, it is important that the essential parameters are estimated correctly. However, this process often faces few problems like when the number of unknown parameters increase, trapping of data in the local minima, repeated exposure to bad results during the search process and occurrence of noisy data. Thus, this paper intends to present an improved bee memory differential evolution (IBMDE) algorithm to solve the mentioned problems. This is a hybrid algorithm that combines the differential evolution (DE) algorithm, the Kalman filter, artificial bee colony (ABC) algorithm, and a memory feature. The aspartate and threonine biosynthesis pathway, and cell cycle pathway are the metabolic pathways used in this paper. For three production simulation pathways, the IBMDE managed to robustly produce the estimated optimal kinetic parameter values with significantly reduced errors. Besides, it also demonstrated faster convergence time compared to the Nelder–Mead (NM), simulated annealing (SA), the genetic algorithm (GA) and DE, respectively. Most importantly, the kinetic parameters that were generated by the IBMDE have improved the production rates of desired metabolites better than other estimation algorithms. Meanwhile, the results proved that the IBMDE is a reliable estimation algorithm.

The Design of Avionics System Interfaces Emulation and Verification Platform Based on QAR Data

2014 ◽  
Vol 668-669 ◽  
pp. 879-883 ◽  
Author(s):  
Yi Gang Sun ◽  
Li Sun
Keyword(s):  
Mathematical Modeling ◽  
Theoretical Data ◽  
Environmental Data ◽  
Input Output ◽  
Output Data ◽  
Running Performance ◽  
Excitation Signal ◽  
Data Platform ◽  
System Verification ◽  
System Interfaces

In order to avoid the complex mathematical modeling and ensure the reliability of avionics system verification, this paper has designed an interfaces emulation and verification platform of avionics system based on QAR data. Platform includes 2 parts: Emulator and Simulator. Simulator generates the flight environmental data which is come from QAR and transforms the data into excitation signal of devices. Emulator emulates the interface features of avionic devices according to the ICD and can be replaced with real devices. By comparing the actual input-output data of devices with QAR theoretical data, this platform can evaluate the running performance of avionic systems or devices and the rationality of the ICD.

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