We propose statistical abduction as a rst-order logical framework for representing, inferring and learning probabilistic knowledge. It semantically integrates logical abduction with a parameterized distribution over abducibles. We show that statistical abduction combined with tabulated search provides an e cient algorithm for probability computation, a Viterbi-like algorithm for nding the most ...

the air transport industry is seeking to manage risks in air travels. its main objective is to detect abnormal behaviors in various flight conditions. the current methods have some limitations and are based on studying the risks and measuring the effective parameters. these parameters do not remove the dependency of a flight process on the time and human decisions. in this paper, we used an hmm...

Many problems in scientific research and engineering applications can be decomposed into the constrained optimization problems. Most of them are the nonlinear programming problems which are very hard to be solved by the traditional methods. In this paper, an electromagnetism-like mechanism (EM) algorithm, which is a meta-heuristic algorithm, has been improved for these problems. Firstly, some m...

Due to the complex nature of training neural network (NN), this problem has gained popularity in the nonlinear optimization field. In order to avoid falling into local minimum because of inappropriate initial weights, a number of global search techniques are developed. This paper applies a novel global algorithm, which is electromagnetism-like mechanism (EM) algorithm, to train NN and the EM ba...

This paper introduces an improved electromagnetism-like algorithm (IEM) for recurrent fuzzy neural controller design. The hybrid IEM algorithm combines the advantages of the electromagnetism-like (EM) algorithm and the genetic algorithm (GA). The proposed IEM is composed of initialization, local search, total force calculation, movement, and evaluation. For recurrent fuzzy neural controller des...

We formulate feature registration problems as maximum likelihood or Bayesian maximum a posteriori estimation problems using mixture models. An EM-like algorithm is proposed to jointly solve for the feature correspondences as well as the geometric transformations. A novel aspect of our approach is the embedding of the EM algorithm within a deterministic annealing scheme in order to directly cont...

Abstract: A comparison study between Electromagnetism-Like Algorithm (EM) and Genetic Algorithm (GA) has been presented in this work to solve the Inverse Kinematics (IK) of a four-link planar robot manipulator. The comparison is focused on some points for both algorithms like the accuracy of the results and the speed of convergence. Different target points have been taken to check the performan...

This paper applies the new developed heuristic electromagnetism-like mechanism (EM) algorithm for the permutation flowshop scheduling problem. This algorithm simulates the electromagnetism theory by considering each solution as an electrical charge. Through the attraction-repulsion of the charges, solutions move to the optimality without being trapped into local optima. We make use of random ke...

Electromagnetism-like algorithm (EM) is a population-based metaheuristic which has been proposed to solve continuous problems effectively. In this paper, we present a new meta-heuristic that uses the EM methodology to solve the single machine scheduling problem. Single machine scheduling is a combinatorial optimization problem. Schedule representation for our problem is based on random keys. Be...

EIT has been used for the dynamic estimation of organ boundaries. One specific application in this context is the estimation of lung boundaries during pulmonary circulation. This would help track the size and shape of lungs of the patients suffering from diseases like pulmonary edema and acute respiratory failure (ARF). The dynamic boundary estimation of the lungs can also be utilized to set an...