Spatial prediction of rainfall-induced shallow landslides using hybrid integration approach of Least-Squares Support Vector Machines and differential evolution optimization: a case study in Central Vietnam

This study represents a hybrid intelligence approach based on the differential evolution optimization and Least-Squares Support Vector Machines for shallow landslide prediction, named as DE–LSSVM_SLP. The LSSVM is used to establish a landslide prediction model whereas the DE is adopted to search the optimal tuning parameters of the LSSVM model. In this research, a GIS database with 129 historical landslide records in the Quy Hop area (Central Vietnam) has been collected to establish the hybrid model. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to assess the performance of the newly constructed model. Experimental results show that the proposed model has high performances with approximately 82% of AUCs on both training and validating datasets. The model’s results were compared with those obtained from other methods, Support Vector Machines, Multilayer Perceptron Neural Networks, and J48 Decision Trees. The result comparison demonstrates that the DE–LSSVM_SLP deems best suited for the dataset at hand; therefore, the proposed model can be a promising tool for spatial prediction of rainfall-induced shallow landslides for the study area.     

Evaluation of Two Low‐Cost–High‐Performance Adsorbent Materials in the Waste‐to‐Product Approach for the Removal of Pesticides from Drinking Water

This study evaluates the performance of two low cost and high performance adsorption materials, i.e., activated carbon produced from two natural waste products: Bamboo and coconut shell, in the removal of three pesticides from drinking water sources. Due to the fact that bamboo and coconut shell are abundant and inexpensive materials in many parts of the world, they respond to the “low‐cost” aspect. The adsorption capacities of two local adsorbents have been compared with commercial activated carbon to explore their potential to respond to the “high quality” aspect. Two pesticides were selected, namely dieldrin and chlorpyrifos, because they are commonly used in agriculture activities, and may remain in high concentrations in surface water used as drinking water sources. The results indicate that the adsorption of pesticides on activated carbons is influenced by physico‐chemical properties of the activated carbon and the pesticides such as the presence of an aromatic ring, and their molar mass. The activated carbon produced from bamboo can be employed as low‐cost and high performance adsorbent, alternative to commercial activated carbon for the removal of pesticides during drinking water production. The performance of activated carbon from bamboo was better due to its relatively large macroporosity and planar surface. The effect of adsorbent and pesticide characteristics on the performance was derived from batch experiments in which the adsorption behavior was studied on the basis of Freundlich isotherms.     

The roles of the reversibility and irreversibility of capillary bonds on the impact dynamics of agglomerates

Acta Geotechnica - Wet agglomerates such as iron-ores, tablets, and aggregates are omnipresent in multi–field industries. However, our understanding of the impact dynamics of these materials...