Bayesian optimization has become a successful tool for hyperparameter optimization of machine learning algorithms, such as support vector machines or deep neural networks. Despite its success, for large datasets, training and validating a single configuration often takes hours, days, or even weeks, which limits the achievable performance. To accelerate hyperparameter optimization, we propose a ...

optimization of reservoir parameters is an important issue in petroleum exploration and production. the ant colony optimization(aco) is a recent approach to solve discrete and continuous optimization problems. in this paper, the ant colony optimization is usedas an intelligent tool to estimate reservoir rock properties. the methodology is illustrated by using a case study on shear wave velocity...

This paper considers identical parallel machines scheduling problem with past-sequence-dependent setup times, deteriorating jobs and learning effects, in which the actual processing time of a job on each machine is given as a function of the processing times of the jobs already processed and its scheduled position on the corresponding machine. In addition, the setup time of a job on each machin...

Whenever an electrical machine is meant to be fed by a power converter, the design should be approached as a system optimization, more than a simple machine sizing. A great variety of electrical machines is available to accomplish this goal, and the task of comparing the different options can be very difficult. A general purpose sizing equation, easily adjustable for every topology, that could ...

Kinematics of a particular five-axis milling machine can drastically change the machining accuracy. Therefore, the reduction of the kinematics error is an important problem associated with the tool path planning. Our newoptimizationmethod employs a closed formof the kinematics error represented as a function of the positions of the cutter contact points. The closed form is derived from the inve...

Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in the computer integrated manufacturing (CIM) environment. A good process plan of a part is built up based on two elements: (1) optimized sequence of the operations of the part; and (2) optimized selection of the machine, cutting tool and tool access direc...

The dynamics in single machine been connected to an infinite power system bus is analyzed in this paper. This analysis requires certain amount of system modeling level. The main components of the system models are excitation system, synchronous machine and the Power System Stabilizer. The Simulink /Matlab are used as the programming tool for analyzing this system performance. Design optimizatio...

In this invited talk at the European Symposium on Algorithms (ESA), 2017, I will discuss a tool called sketching, which is a form of data dimensionality reduction, and its applications to several problems in high dimensional geometry. In particular, I will show how to obtain the fastest possible algorithms for fundamental problems such as projection onto a flat, and also study generalizations o...

This paper presents an approach for a holistic simulation of forging processes considering the interactions between forging press, tooling system and forging process. It can be used in coupled simulations and will enable industrial users in forging industry to do simulation-aided tool optimizations in the design stage of newly developed forging dies. The final aim is to reduce the time-consumin...

As an effective tool in pattern recognition and machine learning, support vector machine (SVM) has been adopted abroad. In developing a successful SVM classifier, eliminating noise and extracting feature are very important. This paper proposes the application of kernel Principal Component Analysis (KPCA) to SVM for feature extraction. Then PSO Algorithm is adopted to optimization of these param...