Dawid Ewald

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

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 Kosiński 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.

Approach to Solve a Criteria Problem of the ABC Algorithm Used to the WBDP Multicriteria Optimization

This article describes the use of the bees algorithm for optimization of the multi-object structure of a welded beam. This problem has been used as a benchmark of the bees algorithm. This article presents an approach to improve the ABC algorithm criteria used for the WBDP multicriteria optimization. The contents of the article show the analysis of the problem, conducted based on the mathematical calculations of the beam dimensions. The further part constitutes a comparison of the received results with the results of the ABC operation. Based on the standards, an additional criterion was established, which verifies the correctness of the results.

Proposed CAEva Simulation Method for Evacuation of People from a Buildings on Fire

This paper presents practical applications of the cellular automata theory for building fire simulation using the CAEva method. Thanks to the tests carried out using appropriately configured program, realistic results of simulated evacuation of people from the building have been achieved. The paper includes the references to actual fire disasters and provides numbers of their resulting casualties. Using such a kind of predication in civil engineering should increase the fire safety of buildings. Simulations described in this paper seem to be very useful, particularly in case of building renovation or temporary unavailability of escape routes. Using them, it is possible to visualize potential hazards and to avoid increased risk in case of fire. Inappropriate operation of buildings, including insouciant planning of renovations are among frequent reasons of tragic accidents cited by fire brigade information services. Similar problems are encountered by inspectors who assess spontaneous fire accidents or arsons during mas events, where wrong safety procedures or inappropriate attempts to cut costs resulted in tragedy. Thanks to the proposed solutions it shall be easier to envisage consequences of problematic decisions causing temporary or permanent unavailability of escape routes. This is exactly the problem analyzed by this paper. It does not take into account, by the rule, the influence of \(\mathrm{CO}_{2}\) and other gases on evacuation difficulty. The described method has been analyzed using descriptions of real life fires, the participants of which were neither asleep nor asphyxiated with carbon monoxide, while the escape was hindered by fire, room layout as well as stress and number of the event participants. The results achieved for such conditions are approximate to the actual (reallife) outcomes, which proved the method to be correct.

Approach to the Monitoring of Energy Consumption in Eco-grinder Based on ABC Optimization

This article is a part of the series dedicated to AI Methods Inspired by Nature and their implementation in the mechatronic systems. The Artificial Bee Colony (ABC) enables the optimization of the consumption of power supplied from photovoltaic cells. The paper includes a few implementations of ABC. Special emphasis was put on maintaining proper energetic balance, and on monitoring of power demand as well as energy sources used for the comminution. The ecological grinder was designed based on the autonomic unit. It can be called autonomous, because it does not need external control. The built-in computer system ensures monitoring and visualization of the current state of the energetic balance.

Practical Application of OFN Arithmetics in a Crisis Control Center Monitoring

In this paper there is a comparision of fuzzy arithmetic calculations in two different notations. The first is well-known L-R notation proposed by Dubois-Prade. It is well known for the researchers who deal with fuzzy logic. The second if OFN notation. This notation was introduced by Kosinski. The same data was used for comparative calculations using the benchmark “Dam and Crisis control center paradox”. There was an observation of water level at the dam with two trends: when the water level increases and decreases. This could cause the different short-term forecast for mentioned situation. The result which was achieved using two different fuzzy arithmetic showed, that OFN notation is sensitive to the trend differences. The authors showed that it provides an extra value which is a relationship between the fuzzy logic and the trend of the observer phenomena.

A New MGlaber Approach as an Example of Novel Artificial Acari Optimization

The proposed MGlaber method is based on observation of the behavior of mites called Macrocheles glaber (Muller, 1860). It opens the series of optimization methods inspired by the behavior of mites, which we have given a common name: Artificial Acari Optimization. Acarologists observed three stages the ovoviviparity process consists of, i.e.: preoviposition behaviour, oviposition behaviour (which is followed by holding an egg below the gnathosoma) and hatching of the larva supported by the female. It seems that the ovoviviparity phenomenon in this species is favoured by two factors, i.e.: poor feeding and poor quality of substrate. Experimental tests on a genetic algorithm were carried out. The MGlaber method was worked into a genetic algorithm by replacing crossig and mutation methods. The obtained results indicate to significant increase in the algorithm convergence without side-effects in the form of stopping of evolution at local extremes. The experiment was carried out one hundred times on random starting populations. No significant deviations of the measured results were observed. The research demonstrated significant increase in the algorithm operation speed. Convergence of evolution has increased about ten times. It should be noted here that MGlaber method was not only or even not primarily created for genetic algorithms. The authors perceive large potential for its application in all optimization methods where the decision about further future of the solutions is taken as a result of the evaluation of the objective function value. Therefore the authors treat this paper as the beginning of a cycle on Artificial Acari Optimization, which will include a series of methods inspired by behaviour of different species of mites.

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

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.

Optimization of Fuel Consumption in Firefighting Water Capsule Flights of a Helicopter

This article presents a possible use of ABC method for optimization of fuel consumption of helicopter which transport water capsule. There are lot of attibutes of flight e.g. the mass of the capsule, velocity, altitude, aerodynamic coefficients of the capsule, and horizontal and vertical winds. The presented method is focused on mentioned attributes. The problem is very important because helicopters are used in real hughe fire and it will be quite good if the fueal needed for this will be as low as possible. That is why authors presents theoretical models of flight of a bag filled with water which is then dropped from an aircraft moving horizontally. The resulet achived by numerical computations are later compared with the results measured for the trajectory of a capsule of water dropped from a helicopter. There ia also a discussion of the experimental and numerical results achieved in mentioned experiment.

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

Abstract The article presents a new multi-criteria optimization method called Artificial Acari Optimization (AAO). AAO method was tested with five well-known benchmark structural problems i.e.: welded beam, pressure vessel, speed reducer, spring design and gear train problem. The results were compared on other representatives of Swarm Intelligence mainstream which are bee algorithms MBO, BCO and ABC. Numerous references show dominance of ABC over MBO and BCO. To check this, a detailed comparisons of AAO results were made and introduced together with the results of the ABC algorithm.

The CutMAG as a New Hybrid Method for Multi-edge Grinder Design Optimisation

This article is a part of the series dedicated to AI Methods Inspired by Nature and their implementation in the mechatronic systems. The CutMAG algorithm uses hybrid approach to optimisation, i.e. a combination of classic genetic algorithms (GA) with morphologic optimisation (M) thus creating innovative approach to optimisation of cutting disk design (Cut) for the multi-edge grinder. The input data include population of individuals. Each individual is represented by a set of cutting disks. Whereas the fitness function was assumed as a combination of several postulates of the mechanical design foundations. The method includes mechanical, design and energy aspects. Each individual constitutes a complete solution of the disk set whereas the population represents the entire class of solutions. The fitness function of an individual is calculated as the average fitness of each disk supplemented by information describing the relationship between both adjacent disks. The method for calculation of function values was selected so as to ensure its maximisation in the process of evolution. Although promising results of the genetic algorithms operation were achieved, one can consider further improvement of the method efficiency. The authors used morphological operations in order to better adopt the method to the task.