# Using an Opportunity Matrix to Select Centers for RBF Neural Networks
## 2 Materials and Methods
### The Opportunity Matrix RBF Center Selection Algorithm
* [PERSON] (1989) [PERSON]; [PERSON] Fast Learning in Networks of Locally Tuned Processing Units. _Neural Comput._**1989**, \(1\), 281-294. [CrossRef] [PERSON] _Neural Networks for Signal Processing_; Prentice Hall: Englewood Cliffs, NJ, USA, 1992. * [PERSON] (1991) [PERSON]; [PERSON] Universal Approximation using Radial-Basis-Function Networks. _Neural Comput._**1991**, \(3\), 246-257. [CrossRef] [PubMed]
* [PERSON] et al. (2002) [PERSON]; [PERSON]; [PERSON]; [PERSON] Effects of Moving the Centers in an RBF Network. _IEEE Trans. Neural Netw._**2002**, _13_, 1299-1307. [CrossRef] [PubMed]
* [PERSON] (2003) [PERSON] _Probability Theory. The Logic of Science_; Cambridge University Press: Cambridge, UK, 2003. * [PERSON] (2010) [PERSON] Clustering: A Neural Network Approach. _Neural Netw._**2010**, _23_, 89-107. [CrossRef] [PubMed]
* [PERSON] and [PERSON] (2006) [PERSON]; [PERSON] _Neural Networks in a Softcomputing Framework_; Springer: London, UK, 2006. * [PERSON] (2003) [PERSON]; [PERSON]; [PERSON] _Model Assisted Survey Sampling_; Springer: New York, NY, USA, 2003. * [PERSON] (1972) [PERSON] _Applied Nonlinear Programming_; McGraw-Hill: New York, NY, USA, 1972. * [PERSON] and [PERSON] (2013) [PERSON]; [PERSON], [PERSON] A Literature Survey of Benchmark Functions for Global Optimisation Problems. _Int. J. Math. Model. Numer. Optim._**2013**, \(4\), 150-194. [CrossRef]
* [PERSON] (1967) [PERSON] _Handbook of the Poisson Distribution_; John Wiley & Sons: New York, NY, USA, 1967. * [PERSON] (1908) Student. The Probable Error of a Mean. _Biometrika_**1908**, \(6\), 1-25. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON] Efficient Energy Consumption Prediction Model for a Data Analytic-Enabled Industry Building in a Smart City. _Build. Res. Inf._**2021**, _49_, 127-143. [CrossRef]
* [PERSON] et al. (2023) [PERSON]; [PERSON]; [PERSON] _The UCI Machine Learning Repository_; University of California, Irvine: Irvine, CA, USA, 2023. * [PERSON] et al. (2020) [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; et al. SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. _Nat. Methods_**2020**, _17_, 261-272. [CrossRef]
* [PERSON] et al. (1972) [PERSON]; [PERSON]; [PERSON] _Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables_; Wiley: New York, NY, USA, 1972. * [PERSON] (2013) [PERSON] _All of Statistics: A Concise Course in Statistical Inference_; Springer: New York, NY, USA, 2013. * [PERSON] (2014) [PERSON]; [PERSON] Adam: A method for stochastic optimization. _arXiv_**2014**, arXiv:1412.6980. * Google (2023) Google. _Google Colaboratory_; Alphabet, Inc.: Mountain View, CA, USA, 2023. * [PERSON] (1947) [PERSON] The Generalization of \"Student's\" Problem When Several Different Population Variances are Involved. _Biometrika_**1947**, 34, 28-35. [CrossRef] [PubMed]
* [PERSON] et al. (2009) [PERSON]; [PERSON]; [PERSON]; [PERSON] NP-Hardness of Euclidean Sum-of-Squares Clustering. _Mach. Learn._**2009**, _75_, 245-248. [CrossRef]
* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON] A Novel Modular RBF Neural Network Based on a Brain-Like Partition Method. _Neural Comput. Appl._**2020**, _32_, 899-911. [CrossRef]

**Disclaimer/Publisher's Note:** The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.