327 research outputs found
Multi-PBil: an estimation distribution algorithm applied to multimodal optimization problems
The Estimation Distribution Algorithms (EDAs) compose an evolutionary metaheuristic whose main characteristic is the construction of solutions in randomly form, using a distribution of probabilities that evolves during the execution.
The Population-Based Incremental Learning Algorithm (PBIL) is a type of EDA where the variables are independent, that is, they do not have significant interactions between themselves. The PBIL considers that the solutions can be represented as vectors of discrete variables, what makes it more adequate for combinatorial optimization problems. This paper presents a method called Multi-PBil that is an extension of PBIL with applications in multimodal problems. The Multi-PBil was developed with the goal to have an efficient and non expensive algorithm of search in multimodal spaces. From PBIL, it was implemented a routine that allows the Multi-PBil to create a probability model to act in the search space. A formula that allows initiating the probability models in regions of the search space next to the searched global points was applied in the process of the probability model initialization rule. The Multi-PBil method was tested and analyzed, presenting some experimental results that highlight its viability and characteristics. It is also shown a comparison of the performance between the Multi-PBil and a traditional Genetic Algorithm using the sharing method.VII Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI
AN INVESTIGATION INTO AN EXPERT SYSTEM FOR TELECOMMUNICATION NETWORK DESIGN
Many telephone companies, especially in Eastern-Europe and the 'third world', are
developing new telephone networks. In such situations the network design engineer needs
computer based tools that not only supplement his own knowledge but also help him to cope
with situations where not all the information necessary for the design is available. Often
traditional network design tools are somewhat removed from the practical world for which
they were developed. They often ignore the significant uncertain and statistical nature of the
input data. They use data taken from a fixed point in time to solve a time variable problem,
and the cost formulae tend to be on an average per line or port rather than the specific case.
Indeed, data is often not available or just plainly unreliable. The engineer has to rely on
rules of thumb honed over many years of experience in designing networks and be able to
cope with missing data.
The complexity of telecommunication networks and the rarity of specialists in this area often
makes the network design process very difficult for a company. It is therefore an important
area for the application of expert systems. Designs resulting from the use of expert systems
will have a measure of uncertainty in their solution and adequate account must be made of
the risk involved in implementing its design recommendations.
The thesis reviews the status of expert systems as used for telecommunication network
design. It further shows that such an expert system needs to reduce a large network problem
into its component parts, use different modules to solve them and then combine these results
to create a total solution. It shows how the various sub-division problems are integrated to
solve the general network design problem. This thesis further presents details of such an
expert system and the databases necessary for network design: three new algorithms are
invented for traffic analysis, node locations and network design and these produce results
that have close correlation with designs taken from BT Consultancy archives.
It was initially supposed that an efficient combination of existing techniques for dealing with uncertainty
within expert systems would suffice for the basis of the new system. It soon
became apparent, however, that to allow for the differing attributes of facts, rules and data
and the varying degrees of importance or rank within each area, a new and radically different
method would be needed.
Having investigated the existing uncertainty problem it is believed that a new more rational
method has been found. The work has involved the invention of the 'Uncertainty Window'
technique and its testing on various aspects of network design, including demand forecast,
network dimensioning, node and link system sizing, etc. using a selection of networks that
have been designed by BT Consultancy staff. From the results of the analysis, modifications
to the technique have been incorporated with the aim of optimising the heuristics and
procedures, so that the structure gives an accurate solution as early as possible.
The essence of the process is one of associating the uncertainty windows with their relevant
rules, data and facts, which results in providing the network designer with an insight into the
uncertainties that have helped produce the overall system design: it indicates which sources
of uncertainty and which assumptions are were critical for further investigation to improve
upon the confidence of the overall design. The windowing technique works by virtue of its
ability to retain the composition of the uncertainty and its associated values, assumption, etc.
and allows for better solutions to be attained.BRITISH TELECOMMUNICATIONS PL
Text Similarity Between Concepts Extracted from Source Code and Documentation
Context: Constant evolution in software systems often results in its documentation losing sync with the content of the source code. The traceability research field has often helped in the past with the aim to recover links between code and documentation, when the two fell out of sync. Objective: The aim of this paper is to compare the concepts contained within the source code of a system with those extracted from its documentation, in order to detect how similar these two sets are. If vastly different, the difference between the two sets might indicate a considerable ageing of the documentation, and a need to update it. Methods: In this paper we reduce the source code of 50 software systems to a set of key terms, each containing the concepts of one of the systems sampled. At the same time, we reduce the documentation of each system to another set of key terms. We then use four different approaches for set comparison to detect how the sets are similar. Results: Using the well known Jaccard index as the benchmark for the comparisons, we have discovered that the cosine distance has excellent comparative powers, and depending on the pre-training of the machine learning model. In particular, the SpaCy and the FastText embeddings offer up to 80% and 90% similarity scores. Conclusion: For most of the sampled systems, the source code and the documentation tend to contain very similar concepts. Given the accuracy for one pre-trained model (e.g., FastText), it becomes also evident that a few systems show a measurable drift between the concepts contained in the documentation and in the source code.</p
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