AAO as a new strategy in modeling and simulation of constructional problems optimization

The spatial evolution of land use in Jinzhou area was simulated using fuzzy cellular automata to determine all factors influencing urban land use change For this purpose, land use data of multiple sources and remote sensing images from 2003 to 2015 were analyzed The following results were obtained: (1) real land use data and simulation data for 2015 were tested using four indices Under the 5 m × 5 m scale, the model shows good performance for simulation of areas with various land use types (2) Among simulations under four scenarios, the effect of traffic guidance on the development of construction land was more distinct under the economic development mode, which clearly showed the phenomenon of “agglomeration” along major traffic lines (3) Jinshitan Street is adjacent to the sea, and land use changes are significant under the 4th scenario, and thus related departments should pay more attention (4) Shortcomings of conventional cellular automata model in processing complex systems could be mitigated through the integration of fuzzy sets

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Simulating Intraurban Land Use Dynamics under Multiple Scenarios Based on Fuzzy Cellular Automata: A Case Study of Jinzhou District, Dalian

This paper describes the results of experiments concerning the optimization method called OFNAnt. As the benchmarks, the author used the set of files from TSPlib repository which includes well known samples of the travelling salesman problem. The innovation of the proposed method consists in implementation of Ordered Fuzzy Numbers to the decision-making process of individual ant agents. This also made it possible to correlate the colony development optimization with the trend. Previous implementations of the fuzzy logic to such meta heuristics like ant systems came down to fuzzy control over the decision-making process of an ant or fuzzy control of the pheromone release mechanism. Thanks to the proposed method, it was possible to expand the family of solutions with the solutions represented by ants moving outside the main circulation. The improvement was possible thanks to better stress that, according to the OFN arithmetic, was put on their participation in the process as compared to the conventional approach, as the direction of their movement has been opposed to the trend followed by majority of colonies. Final conclusions of the experiment indicate to superiority of methods based on Ant Colony Optimization, and in particular the superiority of OFNAnt method over heuristic methods.

Application of Ordered Fuzzy Numbers in a New OFNAnt Algorithm Based on Ant Colony Optimization

The article presents the owlANT method, which allows us to associate a collection of short text messages with ontology The trails were conducted on the collection of communications by Reuters (the so-called second collection) As the methodological base of the method, a swarm intelligence was used, namely the ant colony optimisation The ants, moving between the ontological nodes [1][2], left their pheromone trace As a result, some branches of relations - after some time in evolution - were marked more strongly than the others On the basis of the intensity of the pheromone trace, one can formulate the strength of relations between the various associations, and - indirectly - also between the associated documents As far as the authors know, no one has so far published research on the application of ACO to the development of similarity measure of text documents with the consideration of their meaning-related embedding in ontology The authors refer to the work [3][4], in which the ACO was used for aggregation of concepts in ontology; however, both the purpose and the method were different in that case The research described in the report will be continued to specify the similarity measures taking into consideration the distance in ontology obtained thanks to the evolutionary processing of the meaning of terms with the use of ACO

A Proposal of the New owlANT Method for Determining the Distance between Terms in Ontology

Intrinsically disorder proteins (IDPs) constitute a significant part of proteins that exist and act in cells of living organisms. IDPs play key roles in central cellular processes and some of them are closely related to various human diseases, like cancer or neurodegenerative disorders. Identification of IDPs and studying their structural characteristics have become an important part of structural bioinformatics and structural genomics. However, growing amount of genomic and protein sequences in public repositories pose a pressure on existing methods for identification of IDPs. Large volumes of protein amino acid sequences need to be analyzed in terms of propensity to form disordered regions, and this task requires novel tools and scalable platforms to cope with this big biological data challenge. In this paper, we show how the identification of disordered regions of 3D protein structures can be efficiently accelerated with the use of Apache Spark cluster established and scaled on the public Cloud. For this purpose, we propose Spark-based meta-predictor (Spark-IDPP), which enables efficient prediction of disordered regions of proteins on a large-scale. Results of our performance tests show that, for large data sets, our method achieves almost linear speedup, when scaling out the computations on the 32-node Spark cluster located in the Azure cloud. This proves that through appropriate partitioning of data and by increasing the degree of parallelism, we can significantly improve efficiency of IDP predictions. Additionally, by using several basic predictors, aggregating their ranks in various consensus modes, and filtering the final outcome with a dedicated fuzzy filter, the Spark-IDPP increases the quality of predictions.

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Spark-IDPP: high-throughput and scalable prediction of intrinsically disordered protein regions with Spark clusters on the Cloud

Presently, one of the main problems of computer networks are Distributed Denial of Service attacks which can block network resources like servers. In order to prevent such situations some mechanisms are needed. This paper gives an overview of the Quality of Services methods. A DDoS attack model is described for development purposes. In conslusion some new QoS features are presented. According to presented features QoS method could be used as a protection tool against DDoS attack which is also proven in this paper. The ability to implement the proposed QoS features has already been partially tested. Presented results suggest that the method could be applied widely in practice.

Quality of Services Method as a DDoS Protection Tool

This paper presents the issue of fuzzy arithmetic calculations in two different notations. The well-known L-R notation proposed by Dubois-Prade, which enjoys a well-earned recognition of the researchers dealing with fuzzy logic was presented on one hand. On the other hand, a OFN notation introduced by Kosinski was discussed. Comparative calculations were performed using the data of the benchmark “Dam and Crisis control center paradox”. That benchmark is available in two versions, where the opposite trend is visible at the dam and at the CCC (Crisis control center). In one of the versions, the water level at the observed area decreases and increases at the dam, while in the other version the situation is opposite. The trend difference detection can aid the short-term forecast of the situation change at the monitored area. Results of the applied calculations in OFN notation show that this arithmetic is sensitive to trend differences related to the order characteristic for those numbers. Relationship between the fuzzy logic and the trend of the observed phenomena is an added value to the generalization of OFN and it is also a good signal for the future development of applications of such fuzzy calculations, being their unique feature at the same time.

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Representation of a trend in OFN during fuzzy observance of the water level from the Crisis control center

This article presents a proposal for a new method of defuzzification a fuzzy controller, which is based on the concept of the golden ratio, derived from the Fibonacci series [1]. The origin of the method was the observation of numerous instances of the golden ratio in such diverse fields as biology, architecture, medicine, and painting. A particular area of its occurrence is genetics, where we find the golden ratio in the very structure of the DNA molecule [2] (deoxyribonucleic acid molecules are 21 angstroms wide and 34 angstroms long for each full length of one double helix cycle). This fact makes the ratio in the Fibonacci series in some sense a universal design principle used by man and nature alike. In keeping with the requirements, the authors of the present study first explain the essential concepts of fuzzy logic, including in particular the notions of a fuzzy controller and a method of defuzzification. Then, they postulate the use of the golden ratio in the process of defuzzification and call the idea the Golden Ratio (GR) Method. In the subsequent part of the article, the proposed GR-based instrument is compared with the classical methods of defuzzification, including COG, FOM, and LOM. In the final part, the authors carry out numerous calculations and formulate conclusions which serve to classify the proposed method. At the end they present directions of further research.

A Proposal for a Method of Defuzzification Based on the Golden Ratio—GR

The physical model of Water Capsule Flight is relatively simple but analytically unsolvable. The input data includes the mass of the capsule, velocity, altitude, aerodynamic coefficients of the capsule, and horizontal and vertical winds. The ABC optimization is focused on those attributes. This article is a part of the series dedicated to Inspired by Nature Methods of AI and their implementation in the mechatronic systems. A bag filled with water is an excellent source of explosion-produced water spray which can be used for extinguishing large fires or for other purposes. The paper presents theoretical models of flight of a bag filled with water, dropped from an aircraft moving horizontally. Results of numerical computations based on this model are compared with results of measurements for the trajectory of a bag dropped from a helicopter. A description of the experimental and numerical setup for this experiment are also discussed.

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Wojciech T. Dobrosielski

Papers

Quality of Services Method as a DDoS Protection Tool

Representation of a trend in OFN during fuzzy observance of the water level from the Crisis control center

A Proposal of the New owlANT Method for Determining the Distance between Terms in Ontology

A Proposal for a Method of Defuzzification Based on the Golden Ratio—GR

New proposed implementation of ABC method to optimization of Water Capsule Flight