تحسين النتائح
ترتيب حسب
من
الى
الصفحة 1
الصفحة 1
Applied mathematics and machine learning
The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed many areas of science and engineering; on the other hand, theoretical discoveries in mathematical algorithms, differential equations, and statistical inferences, to name a few, have provided the foundation for the exploration of new multidisciplinary models for solving practical problems. This Special Issue endeavors to continue the journey that started in our previous Special Issue (Applied Mathematics and Computational Physics) by providing a platform for researchers from both academia and industry, as well as government, to present their new computational methods that have engineering and physics applications.
An Introduction to Efficiency and Productivity Analysis
It is designed to be a "first port of call" for people wishing to study efficiency and productivity analysis. The book provides an accessible introduction to the four principal methods involved: econometric estimation of average response models; index numbers; data envelopment analysis (DEA); and stochastic firontier analysis (SFA). For each method, we provide a detailed introduction to the basic concepts, give some simple numerical examples, discuss some of the more important extensions to the basic methods, and provide references for further reading. In addition, we provide a number of detailed empirical applications using real-world data.
Complex decision making : Theory and practice
The increasingly complex environment of today's world, characterized by technological innovation and global communication, generates myriads of possible and actual interactions while limited physical and intellectual resources severely impinge on decision makers, be it in the public or private domains. At the core of the decision-making process is the need for quality information that allows the decision maker to better assess the impact of decisions in terms of outcomes, nonlinear feedback processes and time delays on the performance of the complex system invoked.
