Predicting The Future By Predicting The Past
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Predicting the Future
The future obviously matters to us. It is, after all, where we'll be spending the rest of our lives. We need some degree of foresight if we are to make effective plans for managing our affairs. Much that we would like to know in advance cannot be predicted. But a vast amount of successful prediction is nonetheless possible, especially in the context of applied sciences such as medicine, meteorology, and engineering. This book examines our prospects for finding out about the future in advance. It addresses questions such as why prediction is possible in some areas and not others; what sorts of methods and resources make successful prediction possible; and what obstacles limit the predictive venture. Nicholas Rescher develops a general theory of prediction that encompasses its fundamental principles, methodology, and practice and gives an overview of its promises and problems. Predicting the Future considers the anthropological and historical background of the predictive enterprise. It also examines the conceptual, epistemic, and ontological principles that set the stage for predictive efforts. In short, Rescher explores the basic features of the predictive situation and considers their broader implications in science, in philosophy, and in the management of our daily affairs.
Predicting the Future
Due to the increased capabilities of microprocessors and the advent of graphics processing units (GPUs) in recent decades, the use of machine learning methodologies has become popular in many fields of science and technology. This fact, together with the availability of large amounts of information, has meant that machine learning and Big Data have an important presence in the field of Energy. This Special Issue entitled “Predicting the Future—Big Data and Machine Learning” is focused on applications of machine learning methodologies in the field of energy. Topics include but are not limited to the following: big data architectures of power supply systems, energy-saving and efficiency models, environmental effects of energy consumption, prediction of occupational health and safety outcomes in the energy industry, price forecast prediction of raw materials, and energy management of smart buildings.
Predicting the Future: Can We Do It? and If Not, Why Not?
Author: Gerard G. Nahum
language: en
Publisher: Archway Publishing
Release Date: 2014-10-31
Yogi Berra, the American baseball legend, stated famously that it is difficult to make predictions, especially about the future. We all try to predict what will occur in our lives. We routinely orchestrate events in the present in an attempt to influence what wed like to see happen in the future. But despite our best efforts, everything doesnt always go according to plan. The question is why? In Predicting the Future: Can We Do It? And If Not, Why Not?, author Dr. Gerard G. Nahum offers a comprehensive answer to this question. He provides a framework of explanation as to why we find ourselves in the situations we do concerning our ability (or inability) to predict and influence the future. Nahum illustrates why the predicaments we encounter often have much more to do with the fundamental physical constraints of the universe that we live in rather than anything man-made. Predicting the Future: Can We Do It? And If Not, Why Not? is intellectually rigorous in its approach and conveys a simple message: the information we can access, the knowledge we gain as a result, and the understandings we develop as a consequence are what we use to make decisions about the way we believe the future is most likely to unfold. This, in turn, informs our perspectives, which impacts our choices, and ultimately influences the actions we take.