We used the so-called deterministic annealing algorithm due to Rose and Gurewitz by the classification of patent documents. A C++ program based on this algorithm was run first on some artificially constructed data and the results were good. Then we tested it on data sets obtained from some already classified patents. The conclusion we reached is that this algorithm provides an alternative class...

introduction: the aim of this innovative study was to regenerate a condition that makes it possible to carry out researches in the field on a variety of resorption. materials and methods: in order to develop apical resorption, the root canals of selected teeth were instrumented and then drilled with #4 gates glidden drills. in the next stage, the teeth were submerged in melted rose wax up to 3 ...

the markowitz issue of optimization can’t be solved by precise mathematical methods such as second order schematization, when real world condition and limitations are considered. on the other hand, most managers prefer to manage a small portfolio of available assets in place of a huge portfolio. it can be analogized to cardinal constrains, that is, constrains related to minimum and maximum curr...

We apply the optimization algorithm Adaptive Simulated Annealing (ASA) to the problem of analyzing data on a large population and selecting the best model to predict the probability that an individual with various traits will have a particular disease. We compare ASA with traditional forward and backward regression on computer simulated data. We find that the traditional methods of modeling are...

In this study, for the loads supplied by three thermic plants, power of thermic plants, supplying the minimum values of the cost of energy used for an hour, have been found with Simulated Annealing (SA) which is a metaheuristic optimasition method. Firstly solution have been found with classical Lagrange Method. Later solution have also been found with SA algorithm. Solutions found with two dif...

We show that simulated annealing search can be used to automatically select parameters and find highly similar data regions using a modified version of the DNA-DNA Sequence Similarity Search program. We call this modified program AutoSimS. We use the average score of high-scoring chains to measure the goodness of the resulting sequence similarity search, and use adaptive simulated annealing to ...

Adaptive simulated annealing (ASA) is a global optimization algorithm based on an associated proof that the parameter space can be sampled much more efficiently than by using other previous simulated annealing algorithms. The author’s ASA code has been publicly available for over two years. During this time the author has volunteered to help people via e-mail, and the feedback obtained has been...

We propose a new graph based strategy for the detection of spatial clusters of arbitrary geometric form in a map of geo-referenced populations and cases. Our test statistic is based on the likelihood ratio test previously formulated by Kulldorff and Nagarwalla for circular clusters. A new technique of adaptive simulated annealing is developed, focused on the problem of finding the local maxima ...

This paper investigates a global search optimisation technique, referred to as the repeated weighted boosting search. The proposed optimisation algorithm is extremely simple and easy to implement. Heuristic explanation is given for the global search capability of this technique. Comparison is made with the two better known and widely used global search techniques, known as the genetic algorithm...