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The feasible choice of a propagation model for a given wireless system depends on environment type among other factors. Thus, it is a crucial decision on radio network planning. This current proposal is a new methodology applied for LTE systems that includes: to find optimal parameters of a propagation model that minimizes Root Mean Square Error (RMSE) and maximizes Grey Relation Grade and Mean Absolute Percentage Error, (GRG-MAPE) in a city-forest environment through the use of metaheuristic optimization such as Cuckoo Search (CS). The results, quantitatively analyzed by RMSE and GRG-MAPE, show a better accuracy of optimized model in comparison with the original version and even with Stanford University Interim (SUI) model.

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In this work, a new method employs Bioinspired Computational (BIC) optimization from the genetic algorithm, bat algorithm, and flower pollination algorithm. Robust and accurate modeling of the input parameters adjusts the propagation models Stanford University Interim, Electronic Communication Committee, and Floating Interception that consider environments with characteristics specifically of urban regions in the Amazon. The lack of research related to the development of propagation models for Amazonian environments motivated this work. Thus, this application proves the effectiveness of using BIC techniques for modeling the communication channel. Measurement campaigns were carried out in the city of Belem, Brazil, for large-scale channel modeling on the frequencies of 1.8 and 2.6 GHz, belonging to the long-term evolution or fourth-generation mobile communications system (4G). After being adjusted by the optimum values calculated by the BIC techniques used, the models showed better results compared to modeling without optimization. Additionally, it was verified an error reduction of about 80% concerning the metrics root-mean-square error and standard deviation.

The shrimps Penaeidae represent one of the most frequent and exploited fishery resources in coastal regions worldwide. In the estuaries of the north coast of Brazil they are caught, even when juveniles, by artisanal fisheries and mostly serving local markets. The objective of this study was to determine the composition, abundance and spatio-temporal distribution of species of Penaeidae shrimp caught in the Curuçá estuary, State of Pará, north coast of Brazil. The samples were collected every two months from July 2003 to July 2004 in eight sampling sites using an otter trawl net when the tide was ebbing. Two profiles were selected to study this area: Muriá tidal creek and the Curuçá River, with four sampling points in each site. A total of 6,158 Penaeidae shrimps, belonging to three species, were obtained. Farfantepenaeus subtilis was the dominant species with 78.5% of the total of shrimps, followed by Litopenaeus schmitti and Xiphopenaeus kroyeri that corresponded to 11.5 and 9.8%, respectively. The highest density of F. subtilis and X. kroyeri was obtained during the rainy season (p <0.05), with a density of 197.4 ind./1,000 m2 and 23.7 ind./1,000 m2 respectively, both in March/04. The white shrimp (L. schmitti) was more abundant in the dry season and had two peaks of larger density in July 2003 (10.4 individuals/1,000 m2), dry season and one second peak in March (16.5 individuals/1,000 m2), rainy season. These results show the importance of the Curuçá estuary for the life cycle and maintenance of coastal stocks of these species.