Research Article | OPEN ACCESS
Bioinspired Engineering and Complex Systems Engineering: A Theoretical Framework for Water Management
Rodriguez Miranda, Juan Pablo, Garcia-Ubaque, Cesar Augusto and Sanchez Cespedes, Juan Manuel
Francisco Jose de Caldas District University, Bogota D.C., Carrera 7 # 40 B-53, 110221, Colombia
Research Journal of Applied Sciences, Engineering and Technology 2018 8:281-287
Received: October 20, 2017 | Accepted: February 7, 2018 | Published: August 15, 2018
Abstract
This study reviews the state of the art of different existing modeling tools applied in management water systems. Initially, is carried a conceptual review of several modeling systems, applied by the scientific community to model phenomena presented in reality. Emphasizing the modeling tools that serve to describe non-linear systems with high levels of complexity, such as Bio-inspired engineering and Complex Systems. Among the tools described are artificial intelligence, bio-inspired algorithms, artificial neuronal network, evolutionary algorithms, fuzzy logic, data mining, Bayesian networks, genetic algorithms, emerging systems, ant colony, particle swarm and cellular automata. Then, a review of scientific articles is carried out, showing how these tools have been used for water management systems, for example, making decision in water resources systems, consumption prediction models, quantity, flow, water quality, also for analysis of water pollution sources and wastewater treatment systems, among others. Then, it presents some future guidelines, in which it proposed that these modeling tools could be very useful for the planning and environmental planning of watersheds. Finally, it concluded that these tools have used to solve problems of water resources optimization but very little in the water environmental planning of a river basin.
Keywords:
Decision making, forecasting models, modeling, neural networks, optimization, water management,
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