Steel lazy wave riser (SLWR) is derived from the simple catenary (SCR) by installation of buoyancy modules on its section. Infinite SLWR configurations are possible, and this poses difficulties in determining best configuration. However, it possible to capture some suitable which satisfy given design criteria specific a project. We referred these as optimum for problem. Several advanced optimiz...

In this paper, optimum design of three-dimensional (3D) multi-story reinforced concrete (RC) structures is obtained using an improved version the plasma generation optimization (IPGO) algorithm. The reinforcing bars and geometry cross-sections are considered as discrete variables that chosen from a prearranged section database. objective function cost framework, steel concrete. moment shear fra...

Learning graphical model parameters from incomplete data is a non-convex optimization problem. Iterative algorithms, such as Expectation Maximization (EM), can be used to get a local optimum solution. However, little is known about the quality of the learned local optimum, compared to the unknown global optimum. We exploit variables that are always observed in the dataset to get an upper bound ...

Tower cost makes up an important part in the whole wind turbine construction especially for offshore farms. The main method to reduce tower is weight by optimum design. This paper proposes a two-level optimization criterion optimal design of steel conical considering different structural reliability and uncertainty, along with discreteness variables such as thickness bolt type. In first level, ...

The main purposes of this study are identification, modeling and ranking of factors influencing the brand hate.  To do this, mixed approaches of qualitative and quantitative have used. In the qualitative approach, the grounded theory method has considered. Hence, the opinions of 18 sale managers in the field of home appliance, as experts, collected and analyzed. The results of analyzing in 3 st...

This paper presents a new method to convert continuous variables into discrete variables for inductive machine learning. The method can be applied to pattern classification problems in machine learning and data mining. The discretization process is formulated as an optimization problem. We first use the normalized mutual information that measures the interdependence between the class labels and...