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EARTHQUAKE SAFE CONSTRUCTION OF MASONRY BUILDINGS

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Ille & Vilaine Tourisme

www.forodelajusticia.com Los días 20 y 21 de Octubre se celebrará el VII Foro de la Justicia, organizado por Ausbanc en la Fundació Joan i Miró en Palma de Mallorca. Los temas serán los derechos turísticos y financieros, y contará con destacadas personalidades en ambas materias que expondrán los principales retos e innovaciones en los dos ámbitos. El VII Foro de la Justicia, organizado en Palma de Mallorca, pondrá el foco en su primera jornada en los derechos turísticos y numerosos aspectos y retos que enfrenta el sector en el ámbito legal y en el de la innovación. Será la jornada más extensa del evento, durante la cual se explorarán las posibilidades para el desarrollo del sector; alternativas al turismo de calidad –productos de turismo deportivo y celebración de eventos-, se analizarán la estacionalidad del sector, sus efectos y propuestas para eliminarla, y el impacto económico y jurídico del turismo en el comercio minorista, efectuándose un análisis comparativo con otras regiones. La reconversión de espacios turísticos y planta hotelera y sus perspectivas de futuro cerrarán la primera mesa del día que se ocupa del turismo para el desarrollo y las nuevas formas de hacer turismo

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SEISMIC PERFORMANCE OF RC BUILDINGS WITH SHEAR WALL

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Flood frequency and its magnitude are essential for the proper design of hydraulics structures such as bridges, spillways, culverts, waterways, roads, railways, flood control structures and urban drainage systems. Since, flood is a very complex natural event depending upon characteristics of catchment, rainfall conditions and various other factors, thus its analytical modelling is very difficult to pursue. Recently, artificial intelligence techniques such as gene expression programming (GEP), artificial neural network (ANN) etc. have been found to be efficient in modelling complex problems in hydraulic engineering. The performance of GEP model has been reported to be better than that of the ANN. Moreover, GEP provides mathematical equation which makes it more superior over other soft computing techniques that do not give any analytical mathematical equation. Therefore, in present study, GEP is implemented in flood frequency analysis for typical Indian river gauging station. The results obtained in the present study are highly promising and suggest that GEP modelling is a versatile technique and represents an improved alternative to the more conventional approach for the flood frequency analysis.

APPLICATION OF GENE EXPRESSION PROGRAMMING IN FLOOD FREQUENCY ANALYSIS

Mohd Danish

The scour modelling in cohesive beds is relatively more complex than that in sandy beds and thus there is limited number of studies available on local scour at bridge abutments on cohesive sediment. Recently, a good progress has been made in the development of data-driven techniques based on artificial intelligence (AI). It has been reported that AI-based inductive modelling techniques are frequently used to model complex process due to their powerful and non-linear model structures and their increased capabilities to capture the cause and effect relationship of such complex processes. Gene Expression Programming (GEP) is one of the AI techniques that have emerged as a powerful tool in modelling complex phenomenon into simpler chromosomal architecture. This technique has been proved to be more accurate and much simpler than other AI tools. In the present study, an attempt has been made to implement GEP for the development of scour depth prediction model at bridge abutments in cohesive sediments using laboratory data available in literature. The present study reveals that the performance of GEP is better than nonlinear regression model for the prediction of scour depth at abutments in cohesive beds.

Prediction of scour depth at bridge abutments in cohesive bed using gene expr...

Mohd Danish

Accurate and reliable estimation of the scour depth at a bridge pier is essential for the safe and economical design of the bridge foundation. The phenomenon of scour at the pier placed on sediments is extremely complex in nature. Only a limited number of studies have been reported on local scour around bridge piers in cohesive sediment mainly due to the fact that scour modeling in cohesive beds is relatively more complex than that in sandy beds. Recent research has made good progress in the development of data-driven technique based on artificial intelligence (AI). It has been reported that AI-based inductive modeling techniques are frequently used to model complex process due to their powerful and non-linear model structures and their increased capabilities to capture the cause and effect relationship of such complex processes. Gene Expression Programming (GEP) is one of the AI techniques that have emerged as a powerful tool in modeling complex phenomenon into simpler chromosomal architecture. This technique has been proved to be more accurate and much simpler than other AI tools. In the present study, an attempt has been made to implement GEP for the development of scour depth prediction model at bridge piers in cohesive sediments using laboratory data available in literature. The present study reveals that the performance of GEP is better than nonlinear regression model for the prediction of scour depth at piers in cohesive beds

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IS 1893:1984

APPLICATION OF GENE EXPRESSION PROGRAMMING IN FLOOD FREQUENCY ANALYSIS

Prediction of scour depth at bridge abutments in cohesive bed using gene expr...

Scour prediction at bridge piers in cohesive bed using gene expression progra...

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