Publisher's Synopsis
Mathematical models arise in a wide variety of fields, including weather forecasting, engineering, business and finance, science, and medicine. The application of computer methods to simulate such models has revolutionized these fields and is one of the most significant achievements of the computer age. Developing and analyzing such models so that the computer simulations can be carried out efficiently and accurately involves more than classical mathematics and elementary computer science. Computational science is the application of computational and numerical techniques to solve large and complex problems. Computational science takes advantage of not only the improvements in computer hardware, but probably more importantly, the improvements in computer algorithms and mathematical techniques. Computational science allows us to do things that were previously too difficult to do due to the complexity of the mathematics, the large number of calculations involved, or a combination of the two. Computational science also allows us to build models that allow us to make predictions of what might happen in the lab, so that we are perhaps better prepared to make good observations or to understand better what we are seeing. We can also use computational techniques to perform experiments that might be too expensive or too dangerous to do in the lab. We can, for example, use computational techniques to predict how a new drug might behave in the body. This allows us to reduce, but not eliminate, the number of animal tests that we might have done prior to the development of computational pharmacology techniques. While computational models cannot replace the lab, they have certainly become an intricate part of the overall search for scientific knowledge. Computer simulations provide both qualitative and quantitative insights into many phenomena that are too complex to be dealt with by analytical methods or too expensive or dangerous to study by experiments. Methods in Computational and Applied Mathematics considers original mathematical contributions to computational methods and numerical analysis with applications mainly related to PDEs. Mathematical models arise in a wide variety of fields, including weather forecasting, engineering, business and finance, science, and medicine. The application of computer methods to simulate such models has revolutionized these fields and is one of the most significant achievements of the computer age. Developing and analyzing such models so that the computer simulations can be carried out efficiently and accurately involves more than classical mathematics and elementary computer science. Computational science is the application of computational and numerical techniques to solve large and complex problems. Computational science takes advantage of not only the improvements in computer hardware, but probably more importantly, the improvements in computer algorithms and mathematical techniques. Computational science allows us to do things that were previously too difficult to do due to the complexity of the mathematics, the large number of calculations involved, or a combination of the two. Computational science also allows us to build models that allow us to make predictions of what might happen in the lab, so that we are perhaps better prepared to make good observations or to understand better what we are seeing. We can also use computational techniques to perform experiments that might be too expensive or too dangerous to do in the lab. We can, for example, use computational techniques to predict how a new drug might behave in the body. This allows us to reduce, but not eliminate, the number of animal tests that we might have done prior to the development of computational pharmacology techniques. While computational models cannot replace the lab, they have certainly become an intricate part of the overall search for scientific knowledge. Computer simulations provide both qualitative and quantitative insights into many phenomena that are too complex to be dealt with by analytical methods or too expensive or dangerous to study by experiments. Methods in Computational and Applied Mathematics considers original mathematical contributions to computational methods and numerical analysis with applications mainly related to PDEs. Mathematical models arise in a wide variety of fields, including weather forecasting, engineering, business and finance, science, and medicine. The application of computer methods to simulate such models has revolutionized these fields and is one of the most significant achievements of the computer age. Developing and analyzing such models so that the computer simulations can be carried out efficiently and accurately involves more than classical mathematics and elementary computer science. Computational science is the application of computational and numerical techniques to solve large and complex problems. Computational science takes advantage of not only the improvements in computer hardware, but probably more importantly, the improvements in computer algorithms and mathematical techniques. Computational science allows us to do things that were previously too difficult to do due to the complexity of the mathematics, the large number of calculations involved, or a combination of the two. Computational science also allows us to build models that allow us to make predictions of what might happen in the lab, so that we are perhaps better prepared to make good observations or to understand better what we are seeing. We can also use computational techniques to perform experiments that might be too expensive or too dangerous to do in the lab. We can, for example, use computational techniques to predict how a new drug might behave in the body. This allows us to reduce, but not eliminate, the number of animal tests that we might have done prior to the development of computational pharmacology techniques. While computational models cannot replace the lab, they have certainly become an intricate part of the overall search for scientific knowledge. Computer simulations provide both qualitative and quantitative insights into many phenomena that are too complex to be dealt with by analytical methods or too expensive or dangerous to study by experiments. Methods in Computational and Applied Mathematics considers original mathematical contributions to computational methods and numerical analysis with applications mainly related to PDEs.
