All a b c d e f g h i j k l m n o p q r s t u v w x y z Other

Previous Page 34 Next

Displaying 661 – 680 of 922

Showing per page

An effective global path planning algorithm with teaching-learning-based optimization

Emad Hazrati Nejad, Sevgi Yigit-Sert, Sahin Emrah Amrahov (2024)

Kybernetika

Due to the widespread use of mobile robots in various applications, the path planning problem has emerged as one of the important research topics. Path planning is defined as finding the shortest path starting from the initial point to the destination in such a way as to get rid of the obstacles it encounters. In this study, we propose a path planning algorithm based on a teaching-learning-based optimization (TLBO) algorithm with Bezier curves in a static environment with obstacles. The proposed...

An efficient algorithm for adaptive total variation based image decomposition and restoration

Xinwu Liu, Lihong Huang (2014)

International Journal of Applied Mathematics and Computer Science

With the aim to better preserve sharp edges and important structure features in the recovered image, this article researches an improved adaptive total variation regularization and H −1 norm fidelity based strategy for image decomposition and restoration. Computationally, for minimizing the proposed energy functional, we investigate an efficient numerical algorithm-the split Bregman method, and briefly prove its convergence. In addition, comparisons are also made with the classical OSV (Osher-Sole-Vese)...

An evolutionary approach to constraint-regularized learning.

Eyke Hüllermeier, Ingo Renners, Adolf Grauel (2004)

Mathware and Soft Computing

The success of machine learning methods for inducing models from data crucially depends on the proper incorporation of background knowledge about the model to be learned. The idea of constraint-regularized learning is to employ fuzzy set-based modeling techniques in order to express such knowledge in a flexible way, and to formalize it in terms of fuzzy constraints. Thus, background knowledge can be used to appropriately bias the learn ing process within the regularization framework of inductive...

An Exact Method for Solving the Multi-Processor Flow-Shop

Jacques Carlier, Emmanuel Neron (2010)

RAIRO - Operations Research

The aim of this paper is to present a new branch and bound method for solving the Multi-Processor Flow-Shop. This method is based on the relaxation of the initial problem to m-machine problems corresponding to centers. Release dates and tails are associated with operations and machines. The branching scheme consists in fixing the inputs of a critical center and the lower bounds are those of the m-machine problem. Several techniques for adjusting release dates and tails have also been introduced....

An exercise on Fibonacci representations

Jean Berstel (2001)

RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications

We give a partial answer to a question of Carlitz asking for a closed formula for the number of distinct representations of an integer in the Fibonacci base.

Currently displaying 661 – 680 of 922