Familia, estamento e institución: el clero secular en el reino de Córdoba a mediados del siglo XVIII. El caso de Lucena
Resumen Esta aportación forma parte de un proyecto más amplio que actualmente desarrollo, centrado en el estudio de la estructura familiar, económica, social e institucional del clero secular del reino de Córdoba a través de los libros de Familias de Eclesiásticos y libros de Haciendas de Eclesiásticos del catastro del marqués de la Ensenada. Este texto supone precisamente un avance de aquel, a través, en concreto, del núcleo más importante de la Subbética cordobesa por el número de eclesiásticos e instituciones eclesiásticas como fue Lucena durante el Antiguo Régimen, y de solo sus libros de Familias de Eclesiásticos. Consabida fuente emanada de las respuestas particulares de aquella magna encuesta borbónica con la que el gran servidor de Fernando VI quiso conocer la riqueza de sus súbditos de la corona de Castilla para aplicarles la Única Contribución, aquel fondo documental está, sin embargo, muy poco explotado desde la triple perspectiva que aquí se hará –de ahí el interés de esta elaboración, verdadera aportación, pues, a la historiografía modernista–, y que hay que ver, analizar y entender en el contexto de un Estado cada vez más necesitado de saber, fiscalizar y controlar a sus súbditos para gobernar, como fue, en definitiva, el ilustrado. Básica metodología para la obtención de nuestro indicado triple propósito será la cuantificación y el aparato estadístico subsiguiente, indispensable, en este caso, para comprender bien el texto que respalda. Finalmente, una segunda fase centrada en el análisis de los libros de haciendas de eclesiásticos redondearán los resultados que ahora se presentan, por cuanto definirán la situación económica del colectivo examinado.
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M. HU, J. D. JEFFERY, T.WU, Peak load shifting control using a mimetic algorithm, European Journal on Operational Research, 217 (1) (2012), 185-197
ISO 16739 (2013). Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries. The International Organization for Standardization
J. KENNEDY, R. C. EBERHART, Particle swarm optimization, in: IEEE International Conference on Neural Networks, Piscataway, New Jersey, 1995, pp. 1942-1948
G. KONTES, G. GIANNAKIS, E. KOSMATOPOULOS, D.V. ROVAS, Adaptive fine-tuning of building energy management systems using co-simulation, in Proceedings: 2012 IEEE International Conference on Control Applications, Dubrovnik, Croatia, 2012, pp. 1664-1669.
A. K. KORDON, Applied computational intelligence – how to create value, Springer, Berlin Heidelberg, 2007.
K. MACEK, K. MACÍK, A methodology for quantitative comparison of control solutions and its application to HVAC (heating, ventilation and air conditioning) systems, Energy, 44 (1) (2012) 117-125
K. MACEK, V. BICÍK, J. ROJÍCEK, Trajectory optimization under changing conditions through evolutionary approach and black-box models with refining, Advances in Intelligent Systems and Computing 217 (2013) 267-274
K. MACÍK, J. ROJÍCEK, P. STLUKA, J. VASS, Advanced HVAC Control: Theory vs. Reality, in: Preprints of the 18th IVAC World Congress, Milano, Italy, 2011, pp. 3108-3113
F. OLDEWURTEL, A. PARISIO, C. N. JONES, D. GYALISTRAS, M. GWERDER, V. STAUCH, B. LEHMANN, M. MORARI, Use of model predictive control and weather forecasts for energy efficient building climate control, Energy and Buildings, 45 (2012), 15-27
S.J. QIN, T.A. BADGWELL, A survey of industrial model predictive control technology Control Engineering Practice, 11 (2003) 733–764
C. RASMUSSEN, C. K. I. WILLIAMS, Gaussian processes for machine learning, The MIT Press, Cambridge, Massachusetts, 2006
R. ROJAS, Neural networks – a systematic introduction, Springer, Berlin, 1996
J. ROJÍCEK, R. FIŠERA, G.D. KONTES, G.I. GIANNAKIS, D.V. ROVAS, Functional and technological definition of BIM-aware services to Assess, Predict and Optimize energy performance of buildings. In Proceedings 2nd Central European Symposium on Building Physics, Vienna, Austria, September 9-11, 2013. (To Appear)
R. STORN, K. PRICE, Differential evolution – a simple and efficient heuristic for global optimization, Journal of Global Optimization, 11 (1997), 341-359
M. STRELEC, K. MACEK, A. ABATE, Modeling and simulation of a microgrid as a stochastic hybrid system, in: Proceedings of the IEEE PES Innovative Smart Grid Technologies, Berlin, Germany, 2012, pp. 1-9.
C. VALMACEDA, K. KATSIGARAKIS, M.A. GARCIA FUENTES, J. L. HERNANDEZ GARCIA, G.D. KONTES, D.V. ROVAS, An event-driven SOA-based platform for energy-efficiency applications in buildings, CIBW78 2013, Beijing, China (To appear).
L. WASSERMAN, All of nonparametric statistics, Springer, New York, 2006
S. WOLD, Principal component analysis, Chemometrics and Intelligent Laboratory Systems, 2 (1) (1997), 37-52
E. ZACEKOVA, L. FERKL, Building modeling and control using multi-step ahead error minimization, in: Proceedings of Mediterranean Conference Control & Automation, Barcelona, Spain, 2012, pp. 421-426.
M. J. GANCO, R. ALCALA, F.HERRENA, A multi-objective evolutionary algorithm for an effective tuning of fuzzy logic controllers in heating, ventilating and air conditioning systems, Applied Intelligence, 36 (2) (2012), 330-347
GUYON, I., ELISEEFF, A., An introduction to variable and feature selection, The Journal of Machine Learning Research, 3 (2003) 1157-1182
N. HANSEN, A. OSTERMEIER, Adapting arbitrary normal mutation distributions in evolution strategies: The covariance matrix adaptation. in: Proceedings of IEEE International Conference on Evolutionary Computation, Nagoya, Japan, 1996, pp. 312-317
P. HAVES, B. HENCEY, F. BORELLI, J. ELLIOT, Y. MA, B. COFFEY, S. BENGEA, M. WETTER, Model predictive control of HVAC systems: implementation and testing at the University of California, Merced, technical report, Lawrence Berkeley National Laboratory, Berkeley, California, 2010.
G. P. HENZE, S. LIU, Experimental analysis of simulated reinforcement learning control for active and passive building thermal storage inventory: Part 1. theoretical foundation, Energy and Buildings, 38 (2) (2006), 142-147
M. HU, J. D. JEFFERY, T.WU, Peak load shifting control using a mimetic algorithm, European Journal on Operational Research, 217 (1) (2012), 185-197
ISO 16739 (2013). Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries. The International Organization for Standardization
J. KENNEDY, R. C. EBERHART, Particle swarm optimization, in: IEEE International Conference on Neural Networks, Piscataway, New Jersey, 1995, pp. 1942-1948
G. KONTES, G. GIANNAKIS, E. KOSMATOPOULOS, D.V. ROVAS, Adaptive fine-tuning of building energy management systems using co-simulation, in Proceedings: 2012 IEEE International Conference on Control Applications, Dubrovnik, Croatia, 2012, pp. 1664-1669.
A. K. KORDON, Applied computational intelligence – how to create value, Springer, Berlin Heidelberg, 2007.
K. MACEK, K. MACÍK, A methodology for quantitative comparison of control solutions and its application to HVAC (heating, ventilation and air conditioning) systems, Energy, 44 (1) (2012) 117-125
K. MACEK, V. BICÍK, J. ROJÍCEK, Trajectory optimization under changing conditions through evolutionary approach and black-box models with refining, Advances in Intelligent Systems and Computing 217 (2013) 267-274
K. MACÍK, J. ROJÍCEK, P. STLUKA, J. VASS, Advanced HVAC Control: Theory vs. Reality, in: Preprints of the 18th IVAC World Congress, Milano, Italy, 2011, pp. 3108-3113
F. OLDEWURTEL, A. PARISIO, C. N. JONES, D. GYALISTRAS, M. GWERDER, V. STAUCH, B. LEHMANN, M. MORARI, Use of model predictive control and weather forecasts for energy efficient building climate control, Energy and Buildings, 45 (2012), 15-27
S.J. QIN, T.A. BADGWELL, A survey of industrial model predictive control technology Control Engineering Practice, 11 (2003) 733–764
C. RASMUSSEN, C. K. I. WILLIAMS, Gaussian processes for machine learning, The MIT Press, Cambridge, Massachusetts, 2006
R. ROJAS, Neural networks – a systematic introduction, Springer, Berlin, 1996
J. ROJÍCEK, R. FIŠERA, G.D. KONTES, G.I. GIANNAKIS, D.V. ROVAS, Functional and technological definition of BIM-aware services to Assess, Predict and Optimize energy performance of buildings. In Proceedings 2nd Central European Symposium on Building Physics, Vienna, Austria, September 9-11, 2013. (To Appear)
R. STORN, K. PRICE, Differential evolution – a simple and efficient heuristic for global optimization, Journal of Global Optimization, 11 (1997), 341-359
M. STRELEC, K. MACEK, A. ABATE, Modeling and simulation of a microgrid as a stochastic hybrid system, in: Proceedings of the IEEE PES Innovative Smart Grid Technologies, Berlin, Germany, 2012, pp. 1-9.
C. VALMACEDA, K. KATSIGARAKIS, M.A. GARCIA FUENTES, J. L. HERNANDEZ GARCIA, G.D. KONTES, D.V. ROVAS, An event-driven SOA-based platform for energy-efficiency applications in buildings, CIBW78 2013, Beijing, China (To appear).
L. WASSERMAN, All of nonparametric statistics, Springer, New York, 2006
S. WOLD, Principal component analysis, Chemometrics and Intelligent Laboratory Systems, 2 (1) (1997), 37-52
E. ZACEKOVA, L. FERKL, Building modeling and control using multi-step ahead error minimization, in: Proceedings of Mediterranean Conference Control & Automation, Barcelona, Spain, 2012, pp. 421-426.
Familia, estamento e institución: el clero secular en el reino de Córdoba a mediados del siglo XVIII. El caso de Lucena. (2013). Studia Historica: Historia Moderna, 35, 343-369. https://doi.org/10.14201/shhmo201335343369
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