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Oil well placement optimization using niche particle swarm optimization.

Conference Proceeding
Cheng, G., An, Y., Wang, Z., & Zhu, K. (2012)
Oil well placement optimization using niche particle swarm optimization. In Proceedings of CIS'2012 (International Conference on Computational Intelligence and Security), 61-64. https://doi.org/10.1109/CIS.2012.22
A challenging problem in oil field development project is the optimization of multi-wells placement because of the increasing in optimization variable quantities and searching...

On the comparison of initialisation strategies in differential evolution for large scale optimisation

Journal Article
Segredo, E., Paechter, B., Segura, C., & González-Vila, C. I. (2018)
On the comparison of initialisation strategies in differential evolution for large scale optimisation. Optimization Letters, 12(1), 221-234. https://doi.org/10.1007/s11590-017-1107-z
Differential Evolution (DE) has shown to be a promising global opimisation solver for continuous problems, even for those with a large dimensionality. Different previous works...

BayesPiles: Visualisation Support for Bayesian Network Structure Learning

Journal Article
Vogogias, A., Kennedy, J., Archambault, D., Bach, B., Smith, V. A., & Currant, H. (2018)
BayesPiles: Visualisation Support for Bayesian Network Structure Learning. ACM transactions on intelligent systems and technology, 10(1), 1-23. https://doi.org/10.1145/3230623
We address the problem of exploring, combining and comparing large collections of scored, directed networks for understanding inferred Bayesian networks used in biology. In th...

Modelling and Forecasting Human Populations using Sigmoid Models

Thesis
Raeside, R. Modelling and Forecasting Human Populations using Sigmoid Models. (Thesis)
Edinburgh Napier University. Retrieved from http://researchrepository.napier.ac.uk/Output/1053286
Early this century "S-shaped" curves, sigmoids, gained populari ty among demographers. However, by 1940, the approach had "fallen out of favour", being criticised for giving p...

An agent based Bayesian forecasting model for enhanced network security.

Conference Proceeding
Pikoulas, J., Buchanan, W. J., Mannion, M., & Triantafyllopoulos, K. (2001)
An agent based Bayesian forecasting model for enhanced network security. In Proceedings. Eighth Annual IEEE International Conference and Workshop On the Engineering of Computer-Based Systems-ECBS 2001, 247 - 254. https://doi.org/10.1109/ECBS.2001.922429
Security has become a major issue in many organisations, but most systems still rely on operating systems, and a user ID and password system to provide user authentication and...

Eight-node membrane element with drilling degrees of freedom for analysis of in-plane stiffness of thick floor plates

Journal Article
Zhang, H., & Kuang, J. S. (2008)
Eight-node membrane element with drilling degrees of freedom for analysis of in-plane stiffness of thick floor plates. International Journal for Numerical Methods in Engineering, 76(13), 2117-2136. https://doi.org/10.1002/nme.2395
The development of eight-node arbitrary quadrilateral membrane elements with drilling degrees of freedom is presented using the compatible displacement interpolation within th...

On the use of inclusion structure in fuzzy clustering algorithm in case of Gaussian membership functions

Journal Article
Nefti-Meziani, S., Oussalah, M., & Soufian, M. (2015)
On the use of inclusion structure in fuzzy clustering algorithm in case of Gaussian membership functions. Journal of Intelligent and Fuzzy Systems, 28(4), 1477-1493. https://doi.org/10.3233/IFS-141407
This article addresses the problem of incorporating an inclusion structure in the general class of fuzzy c-means algorithms. Conventionally, all the classes of fuzzy clusterin...

Proceedings of the 14th International Conference on Scientific and Statistical Database Management.

Conference Proceeding
(2002)
Proceedings of the 14th International Conference on Scientific and Statistical Database Management. In J. Kennedy (Ed.), Proceedings of the 14th International Conference on Scientific and Statistical Database Managementdoi:10.1109/SSDM.2002.1029697
No abstract available.