Adrián Valverde’s research while affiliated with University of Cartagena and other places

The motive of this work is to provide the numerical performances of the reactive transport model that carries trucks with goods on roads by exploiting the stochastic procedures based on the Meyer wavelet (MW) neural network. An objective function is constructed by using the differential model and its boundary conditions. The optimization of the objective function is performed through the hybridization of the global and local search procedures, i.e., swarming and interior point algorithms. Three different cases of the model have been obtained, and the exactness of the stochastic procedure is observed by using the comparison of the obtained and Adams solutions. The negligible absolute error enhances the exactness of the proposed MW neural networks along with the hybridization of the global and local search schemes. Moreover, statistical interpretations based on different operators, histograms, and boxplots are provided to validate the constancy of the designed stochastic structure.

This paper is concerned with mathematical modeling for the development of Shandong traffic. The system dynamics model of the development of traffic in Shandong is established. In terms of this model, it is shown that highway operation as well as rail transit promotes the development of traffic, while traffic accidents inhibit traffic development. Moreover, the maximum error between the output data and the statistics bureau, based on which some forecasts for the development of traffic in the future are given, is obtained, some suggestions and optimization schemes for traffic development are given. Finally, a neural network model of the development of Shandong traffic is also derived.

This research primarily aims at the development of new pathways to facilitate the resolving of the long debated issue of handling ties or the degree of indecisiveness precipitated in comparative information. The decision chaos is accommodated by the elegant application of the choice axiom ensuring intact utility when imperfect choices are observed. The objectives are facilitated by inducing an additional parameter in the probabilistic set up of Maxwell to retain the extent of indecisiveness prevalent in the choice data. The operational soundness of the proposed model is elucidated through the rigorous employment of Gibbs sampling—a popular approach of the Markov chain Monte Carlo methods. The outcomes of this research clearly substantiate the applicability of the proposed scheme in retaining the advantages of discrete comparative data when the freedom of no indecisiveness is permitted. The legitimacy of the devised mechanism is enumerated on multi-fronts such as the estimation of preference probabilities and assessment of worth parameters, and through the quantification of the significance of choice hierarchy. The outcomes of the research highlight the effects of sample size and the extent of indecisiveness exhibited in the choice data. The estimation efficiency is estimated to be improved with the increase in sample size. For the largest considered sample of size 100, we estimated an average confidence width of 0.0097, which is notably more compact than the contemporary samples of size 25 and 50.

This research fundamentally aims at providing a generalized framework to assist the launch of paired comparison models while dealing with discrete binary choices. The purpose is served by exploiting the fundaments of the exponential family of distributions. The proposed generalization is proved to cater to seven paired comparison models as members of this newly developed mechanism. The legitimacy of the devised scheme is demonstrated through rigorous simulation-based investigation as well as keenly persuaded empirical evaluations. A detailed analysis, covering a wide range of parametric settings, through the launch of Gibbs Sampler—a notable extension of Markov Chain Monte Carlo methods, is conducted under the Bayesian paradigm. The outcomes of this research substantiate the legitimacy of the devised general structure by not only successfully retaining the preference ordering but also by staying consistent with the established theoretical framework of comparative models.