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The mergers and acquisitions (M&A) performance measurement is an important tool to test the M&A effects, evaluate the validity of M&A decision-making, and which is an important part in the M&A management. But how to measure the M&A performance is a major issue that troubled many enterprises. This paper overcomes the shortcoming of tradition linear M&A measuring methods, proposes...
Research and development activities (R&D) as the core competitiveness in the high-tech enterprises play an extremely important role and far-reaching significance. If the high-tech enterprises want to realize the effective management to the R&D activities, and improve their success rate and economic benefits, it is necessary to conduct a scientific evaluation for the R&D performance. To...
To evaluate the enterprises' strategic management performance scientifically and accurately, this paper proposes the improved BP neural network model based on Kirkpatrick model which imports the adjustable activation function and the Levenberg-Marquardt optimization algorithm. The improved model not only can simulate the expert in evaluating the strategic performance and avoiding the subjective mistakes...
The agricultural information level is on the initial stage in Hebei province, so we should pay more attention to its construction. And on this basis we can find out the influencing factors and corresponding countermeasures. To evaluate the agricultural information degree in Hebei province scientifically and accurately, this paper proposes the improved BP neural network model which imports the adjustable...
The agricultural information level is on the initial stage in China, so we should pay more attention to its construction, but how to measure the agricultural information degree is a major issue. This paper overcomes the shortcoming of traditional linear agricultural information degree evaluation method, proposes a BP neural network evaluating method based on the multistage dynamic fuzzy judgment,...
For the particularity of electric power enterprises themselves, the commonly methods used to forecast their financial risk is limited and inadequate. To forecast the financial risk of the power enterprises scientifically and accurately, this paper proposes the improved BP neural network imports the adjustable activation function and Levenberg -Marquardt optimization algorithm. The improved model not...
The power projects face the uncertain external environment, they are complex of the projects themselves and the capabilities of the designers, erectors and operator are limited, which make the risk indicators of the power projects investment are extremely complicated, including financial risk, technology risk, production risk, market risk, management risk and environmental risk In order to evaluate...
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