@article {165, title = {Complexity of lakes in a latitudinal gradient}, journal = {Ecological Complexity}, volume = {31}, year = {2017}, month = {9}, pages = {1{\textendash}20}, abstract = {Measuring complexity is fast becoming a key instrument to compare different ecosystems at various scales in ecology. To date there has been little agreement on how to properly describe complexity in terms of ecology. In this regard, this manuscript assesses the significance of using a set of proposed measures based on information theory. These measures are as follows: emergence, self-organization, complexity, homeostasis and autopoiesis. A combination of quantitative and qualitative approaches was used in the data analysis with the aim to apply these proposed measures. This study systematically reviews the data previously collected and generated by a model carried out on four aquatic ecosystems located between the Arctic region and the tropical zone. Thus, this research discusses the case of exploring a high level of self-organization in terms of movement, distribution, and quality of water between the northern temperate zone and the tropics. Moreover, it was assessed the significance of the presence of a complex variable (pH) in the middle of the latitudinal transect. Similarly, this study explores the relationship between self-organization and limiting nutrients (nitrogen, phosphorus and silicates). Furthermore, the importance of how a biomass subsystem is affected by seasonal variations is highlighted in this manuscript. This case study seeks to examine the changing nature of how seasonality affects the complexity dynamics of photosynthetic taxa (lakes located in northern temperate zone) at high latitudes, and it also investigates how a high level of self-organization at the tropical zone can lead to increase the amount of planktonic and benthic fish which determines the dynamics of complexity. This research also compares the emerging role of how a biomass subsystem has a highest temporal dynamics compared to he limiting nutrients{\textquoteright} subsystem. In the same way, the results associated to autopoiesis reflect a moderate degree of autonomy of photosynthetic biomass. It is also discussed the case of how complexity values change in the middle of the latitudinal gradient for all components. Finally, a comparison with Tsallis information was carried out in order to determine that these proposed measures are more suitable due to they are independent of any other parameter. Thus, this approach considers some elements closely related to information theory which determine and better describe ecological dynamics.}, keywords = {Autopoiesis, Biocomplexity, Emergence, Homeostasis, Information theory, Self-organization}, isbn = {1476-945X}, doi = {10.1016/j.ecocom.2017.02.002}, url = {http://dx.doi.org/10.1016/j.ecocom.2017.02.002}, author = {Fern{\'a}ndez, Nelson and Aguilar, Jos{\'e} and Pi{\~n}a-Garc{\'\i}a, C. A. and Gershenson, Carlos} } @article {158, title = {Wind speed forecasting for wind farms: A method based on support vector regression}, journal = {Renewable Energy}, volume = {85}, year = {2016}, month = {1}, pages = {790{\textendash}809}, abstract = {In this paper, a hybrid methodology based on Support Vector Regression for wind speed forecasting is proposed. Using the autoregressive model called Time Delay Coordinates, feature selection is performed by the Phase Space Reconstruction procedure. Then, a Support Vector Regression model is trained using univariate wind speed time series. Parameters of Support Vector Regression are tuned by a genetic algorithm. The proposed method is compared against the persistence model, and autoregressive models (AR, ARMA, and ARIMA) tuned by Akaike{\textquoteright}s Information Criterion and Ordinary Least Squares method. The stationary transformation of time series is also evaluated for the proposed method. Using historical wind speed data from the Mexican Wind Energy Technology Center (CERTE) located at La Ventosa, Oaxaca, M{\'e}xico, the accuracy of the proposed forecasting method is evaluated for a whole range of short termforecasting horizons (from 1 to 24 h ahead). Results show that, forecasts made with our method are more accurate for medium (5{\textendash}23 h ahead) short term WSF and WPF than those made with persistence and autoregressive models.}, keywords = {Genetic algorithms, Non-linear analysis, Phase space reconstruction, Support vector regression, Wind speed forecasting}, isbn = {0960-1481}, doi = {http://dx.doi.org/10.1016/j.renene.2015.07.004}, url = {http://www.sciencedirect.com/science/article/pii/S0960148115301014}, author = {Santamar{\'\i}a-Bonfil, G. and Reyes-Ballesteros, A. and Gershenson, C.} } @article {Gershenson:2013, title = {Living in Living Cities}, journal = {Artificial Life}, volume = {In Press}, year = {2013}, abstract = {

This paper presents and overview of current and potential applications of living technology to urban problems. Living technology can be described as technology that exhibits the core features of living systems. These features can be useful to solve dynamic problems. In particular, urban problems concerning mobility, logistics, telecommunications, governance, safety, sustainability, and society and culture are presented, while solutions involving living technology are reviewed. A methodology for developing living technology is mentioned, while self-organizing traffic lights are used as a case study of the benefits of urban living technology. Finally, the usefulness of describing cities as living systems is discussed.

}, keywords = {cities, Self-organization, traffic, transport}, url = {http://arxiv.org/abs/1111.3659}, author = {Carlos Gershenson} } @book {GershensonDCSOS, title = {Design and Control of Self-organizing Systems}, year = {2007}, note = {http://tinyurl.com/DCSOS2007}, publisher = {CopIt Arxives}, organization = {CopIt Arxives}, address = {Mexico}, abstract = {Complex systems are usually difficult to design and control. There are several particular methods for coping with complexity, but there is no general approach to build complex systems. In this book I pro- pose a methodology to aid engineers in the design and control of com- plex systems. This is based on the description of systems as self- organizing. Starting from the agent metaphor, the methodology pro- poses a conceptual framework and a series of steps to follow to find proper mechanisms that will promote elements to find solutions by ac- tively interacting among themselves. The main premise of the method- ology claims that reducing the "friction" of interactions between el- ements of a system will result in a higher "satisfaction" of the system, i.e. better performance. A general introduction to complex thinking is given, since designing self-organizing systems requires a non-classical thought, while prac- tical notions of complexity and self-organization are put forward. To illustrate the methodology, I present three case studies. Self-organizing traffic light controllers are proposed and studied with multi-agent simulations, outperforming traditional methods. Methods for im- proving communication within self-organizing bureaucracies are ad- vanced, introducing a simple computational model to illustrate the benefits of self-organization. In the last case study, requirements for self-organizing artifacts in an ambient intelligence scenario are dis- cussed. Philosophical implications of the conceptual framework are also put forward.}, keywords = {Complexity Theory, Physics, Self-organization}, isbn = {978-0-9831172-3-0}, url = {http://tinyurl.com/DCSOS2007}, author = {Carlos Gershenson} }