@article {863,
	title = {A three-variety automatic and non-intrusive computer vision system for the estimation of orange fruit pH value},
	journal = {Measurement},
	volume = {152},
	year = {2020},
	pages = {107298},
	abstract = {An automatic 3-variety computer vision orange fruit pH value assessment system in the visible-range is presented, including each 100 different color images from Bam, Blood and Thomson orange of which the true pH has been measured and is known in advance. A total of 452 features are extracted from segmented orange color images. Results with repeated trials include: true versus estimated mean pH values, true minus estimated pH values boxplots, fitness regression dispersion plots and various error measure boxplots, for both single orange variety as well as the three-orange varieties altogether (test set), showing consistent results over all three orange varieties. Regression coefficient for pH estimation in Bam, Blood and Thomson orange varieties, were 0.950, 0.935 and 0.957, respectively. Results show that the hybrid ANN-ABC estimates pH values in orange quite similarly among orange varieties, implying that properly pH values estimation is possible for different orange varieties, regardless of orange type.},
	doi = {https://doi.org/10.1016/j.measurement.2019.107298},
	url = {https://www.sciencedirect.com/science/article/pii/S0263224119311625},
	author = {Sabzi, Sajad and Javadikia, Hossein and J I Arribas}
}
@article {SanJos{\'e}Revuelta2016561,
	title = {Three Natural Computation methods for joint channel estimation and symbol detection in multiuser communications},
	journal = {Applied Soft Computing},
	volume = {49},
	year = {2016},
	pages = {561 - 569},
	abstract = {Abstract This paper studies three of the most important optimization algorithms belonging to Natural Computation (NC): genetic algorithm (GA), tabu search (TS) and simulated quenching (SQ). A concise overview of these methods, including their fundamentals, drawbacks and comparison, is described in the first half of the paper. Our work is particularized and focused on a specific application: joint channel estimation and symbol detection in a Direct-Sequence/Code-Division Multiple-Access (DS/CDMA) multiuser communications scenario; therefore, its channel model is described and the three methods are explained and particularized for solving this. Important issues such as suboptimal convergence, cycling search or control of the population diversity have deserved special attention. Several numerical simulations analyze the performance of these three methods, showing, as well, comparative results with well-known classical algorithms such as the Minimum Mean Square Error estimator (MMSE), the Matched Filter (MF) or Radial Basis Function (RBF)-based detection schemes. As a consequence, the three proposed methods would allow transmission at higher data rates over channels under more severe fading and interference conditions. Simulations show that our proposals require less computational load in most cases. For instance, the proposed \{GA\} saves about 73\% of time with respect to the standard GA. Besides, when the number of active users doubles from 10 to 20, the complexity of the proposed \{GA\} increases by a factor of 8.33, in contrast to 32 for the optimum maximum likelihood detector. The load of \{TS\} and \{SQ\} is around 15{\textendash}25\% higher than that of the proposed GA.},
	keywords = {Population diversity},
	issn = {1568-4946},
	doi = {http://dx.doi.org/10.1016/j.asoc.2016.08.034},
	url = {http://www.sciencedirect.com/science/article/pii/S1568494616304288},
	author = {Luis M. San-Jos{\'e}-Revuelta and J I Arribas}
}
