Ultimate Computing

Bearing Capacity of Shallow Foundations on Cohesionless Soils: A Random Forest Based Approach

Determining the ultimate bearing capacity (UBC) is vital for design of shallow foundations. Recently, soft computing methods (i.e. artificial neural networks and support vector machines) have been used for this purpose. In this paper, Random Forest (RF) is utilized as a tree-based ensemble classifier for predicting the UBC of shallow foundations on cohesionless soils. The inputs of model are wi...

Ultimate computing - biomolecular consciousness and nanotechnology

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Evaluation of Methods for Computing Free-Flow Speed and Its ‎Significance in the HCM 2010; Case Study: A Ramp-Weaving Segment

The core methodology of the Highway Capacity Manual (HCM) 2010 for freeway analyses is based on Free-Flow Speed (FFS). Moreover, weaving segments are major elements of freeway facilities that form where two one-way traffic streams intersect by merging and diverging maneuvers. Hence, this study used three different methods to compute FFS of a ramp-weaving segment, and then employed the proposed ...

Formal Models of Computation - The Ultimate Limits of Computing

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The Search for a Practical 'ultimate Laptop': a Comparison of Electronic, Biomolecular and Quantum Computing

Prediction of Ultimate Strain and Strength of FRP-Confined Concrete Cylinders Using Soft Computing Methods

This paper investigates the effectiveness of four different soft computing methods, namely radial basis neural network (RBNN), adaptive neuro fuzzy inference system (ANFIS) with subtractive clustering (ANFIS-SC), ANFIS with fuzzy c-means clustering (ANFIS-FCM) and M5 model tree (M5Tree), for predicting the ultimate strength and strain of concrete cylinders confined with fiber-reinforced polymer...