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Regression models for sediment transport in tropical rivers
Get PDFThe investigation of sediment transport in tropical rivers is essential for planning effective integrated river basin management to
predict the changes in rivers. The characteristics of rivers and sediment in the tropical region are different compared to those of the
rivers in Europe and the USA, where the median sediment size tends to be much more refined. The origins of the rivers are mainly
tropical forests. Due to the complexity of determining sediment transport, many sediment transport equations were recommended
in the literature. However, the accuracy of the prediction results remains low, particularly for the tropical rivers. The majority of
the existing equations were developed using multiple non-linear regression (MNLR). Machine learning has recently been the
method of choice to increase model prediction accuracy in complex hydrological problems. Compared to the conventional
MNLR method, machine learning algorithms have advanced and can produce a useful prediction model. In this research, three
machine learning models, namely evolutionary polynomial regression (EPR), multi-gene genetic programming (MGGP) and M5
tree model (M5P), were implemented to model sediment transport for rivers in Malaysia. The formulated variables for the
prediction model were originated from the revised equations reported in the relevant literature for Malaysian rivers. Among
the three machine learning models, in terms of different statistical measurement criteria, EPR gives the best prediction model,
followed by MGGP and M5P. Machine learning is excellent at improving the prediction distribution of high data values but lacks
accuracy compared to observations of lower data values. These results indicate that further study needs to be done to improve the
machine learning model’s accuracy to predict sediment transport
A Hybrid Genetic Algorithm For Multi-Compartment Vehicle Routing Problem
No full textBu çalışmada, Çok Bölmeli Araç Rotalama Problemi (ÇB-ARP) ele alınmıştır. Günlük hayatta
marketler, firmalar ve kurumlar bazı ürünleri müşterilerine teslim ederken ya da belirli noktalardan
toplarken, bu ürünleri araç içinde farklı bölmelere koymaları gIn this study, a Multi-Compartment Vehicle Routing Problem (MC-VRP) was studied. In daily life,
markets, companies and organizations need to load their certain products into different
compartments in vehicles during the delivery or collecting of these
Architectural parameters that affect energy consumption: A simulation based case study of a patient room
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An architectural literary analysis: Socio-spatial influences of department stores in Zola's novel The Ladies Paradise
Get PDFTourist guides facing the impacts of the pandemic COVID-19
Get PDFThis study reveals the impacts of the COVID-19 outbreak on the profession of tourist guides and offers possible solutions to the industry. The study draws from the recently published studies and guides’ perspectives from 36 countries. E-mail interview is used to collect data between 25 February and 30 May 2020 when the epidemic is spreading rapidly worldwide. The analysis is performed by using MAXQDA Analytics. The study captures events on COVID-19, as guides experience unemployment and trauma, and provides social and practical implications concerning cooperation and collaboration of stakeholders, the occurrence of inequality, and unfairness in the pandemic
Soft innovation in hotel services: case of Izmir City
No full textPurpose The purpose of this paper is to figure out the impacts of soft innovation in the city hotels in general, whereas the focus is on figuring out if there exists a difference in vitality on the components of soft innovation among the hotel categories,Hospitality, Leisure, Sport & TourismSocial Sciences - Other Topic
