Abstract

Abstract
This chapter introduces biased random-key genetic programming, a new metaheuristic for evolving programs. Each solution program is encoded as a vector of random keys, where a random key is a real number randomly generated in the continuous interval [0,1]. A decoder maps each vector of random keys to a solution program and assigns it a measure of quality. A Program-Expression is encoded in the chromosome using a head-tail representation which is later transformed into a syntax tree using a prefix notation rule. The artificial simulated evolution of the programs is accomplished with a biased random-key genetic algorithm. Examples of the application of this approach to symbolic regression are presented.

Abstract
The Internet of Things (IoT) represents a technical innovation that is already starting to play an important role in smarter water management, when a wide variety of sensors are incorporated into intelligent metering equipment and connected through wireless networks throughout the domiciliary water distribution network, being able to measure volume, flow, temperature, pressure, levels of chlorine, salinity and more. Water scarcity, aging or inadequate water distribution infrastructure, population variation, pollution, more intense and frequent droughts and floods, generate pressures that converge on the need to increase global investment in water infrastructures and to develop solutions for the conservation and management of water. The main stakeholders in the water distribution sector are the ones that can benefit most from the use of telemanagement. However, the results of adopting this innovation are contrary to expectations, with a slow change in traditional business models. The objective of this research is the construction of a value model that allows the identification of actors and value markets and the exchange of value related to the adoption of telemanagement in Portugal, having a solid theoretical basis and a real practical validation. Copyright

Abstract

Abstract

Abstract