Differentiation in Differentiation Method and Neural Network to Investigate Different Criteria of Economic Productivity

Abstract

Economic productivity is one of the most important concepts in economics. Increasing economic productivity will boost a society. This study intends to compare the impact of different criteria on the economic productivity of Iranian factories with differential methods and neural networks. The model estimation results using the difference-in-difference method show that exports have a significant positive effect on productivity growth. The model estimation results using the neural network method show that export has a significant positive effect on productivity growth. The presentation of export development variables in two methods of difference in difference and neural networks showed that the level of productivity could be increased well according to the predictability of the neural network.

Estimation of PM10 and SO2 Substances with Extreme Learning Methods for Analysis of Air Pollution in Amasya Province

“…In the future, air pollutants such as 𝑃𝑃𝑁𝑁 2.5 , 𝑁𝑁𝑆𝑆 2 , 𝑆𝑆 3 and 𝑁𝑁𝑆𝑆 can be estimated with the same methods. Artificial neural networks and differentiation in differentiation methods can be used for the prediction of air pollutants [28]. In addition, by estimating 𝑃𝑃𝑁𝑁 2.5 , 𝑃𝑃𝑁𝑁 10 , 𝑆𝑆𝑆𝑆 2 , 𝑁𝑁𝑆𝑆 2 , 𝑆𝑆 3 and 𝑁𝑁𝑆𝑆 pollutants with long short-term memory networks, future predictions can be made in Amasya province and some measures can be taken for air pollution.…”

Knowledge in Medical Prescriptions with the Help of Genetic Fuzzy Hybrid Model

“…During the reading of drug information by nurses and pharmacy officials [6], mistakes are usually made, and sometimes these mistakes are irreparable. For this reason, having a system that can separate people from these mistakes can help patients recover faster [7,8]. The system introduced here is a knowledge discovery system to prevent medication errors.…”