A Fuzzy Inference System for Players Evaluation in Multi-Player Sports: The Football Study Case

Decision support systems often involve taking into account many factors that influence the choice of existing options. Besides, given the expert’s uncertainty on how to express the relationships between the collected data, it is not easy to define how to choose optimal solutions. Such problems also arise in sport, where coaches or players have many variants to choose from when conducting training or selecting the composition of players for competitions. In this paper, an objective fuzzy inference system based on fuzzy logic to evaluate players in team sports is proposed on the example of football. Based on the Characteristic Objects Method (COMET), a multi-criteria model has been developed to evaluate players on the positions of forwards based on their match statistics. The study has shown that this method can be used effectively in assessing players based on their performance. The COMET method was chosen because of its unique properties. It is one of the few methods that allow identifying the model without giving weightings of decision criteria. Symmetrical and asymmetrical fuzzy triangular numbers were used in model identification. Using the calculated derivatives in the point, it turned out that the criteria weights change in the problem state space. This prevents the use of other multi-criteria decision analysis (MCDA) methods. However, we compare the obtained model with the Technique of Order Preference Similarity (TOPSIS) method in order to better show the advantage of the proposed approach. The results from the objectified COMET model were compared with subjective rankings such as Golden Ball and player value.

Identification of Players Ranking in E-Sport

Human activity is moving steadily to virtual reality. More and more, people from all over the world are keen on growing fascination with e-sport. In practice, e-sport is a type of sport in which players compete using computer games. The competitions in games, like FIFA, Dota2, the League of Legends, and Counter-Strike, are prestigious tournaments with a global reach and a budget of millions of dollars. On the other hand, reliable player ranking is a critical issue in both classic and e-sport. For example, the “Golden Ball” is the most valuable prize for an individual football player in the whole football history. Moreover, the entire players’ world wants to know who the best player is. The position of each player in the ranking depends on the assessment of his skills and predispositions. In this paper, we studied identification of players evaluation and ranking obtained using the multiple-criteria decision-making based method called Characteristic Objects METhod (COMET) on the example of the popular game Counter-Strike: Global Offensive (CS: GO). We present a range of advantages of the player evaluation model created using the COMET method and, therefore, prove the practicality of using multi-criteria decision analysis (MCDA) methods to build multi-criteria assessment models in emerging areas of eSports. Thus, we provide a methodical and practical background for building a decision support system engine for the evaluation of players in several eSports.

Development of technology for a fermented drink with cancer protective properties

Some plant sources of biologically active substances particularly cruciferous vegetables, both in native form and as extracts, display effects towards carcinogenesis that make these food sources cancer protective and recurrence preventive agents. In the currently developing tendency towards functional foodstuffs like dairy products targeted at nutritional-dependent diseases, development of a dairy beverage containing sulforaphane deserves attention. Creating a recipe for such a product includes: selecting a plant sulforaphane source, testing its compatibility with the milk base, choosing the addition dosage and methods and experimental beverage preparation. In pursuit of these goals in the study, firstly, turnip (Brassica rapa l.) root, an affordable sulforaphane provider, was chosen. Glucoraphanin content in various turnip varieties was determined and the Golden Ball variety selected. Sulforaphane was introduced to milk in turnip purée and aqueous extract forms. The effect of purée/extract dosage on milk fermentation process and the final producťs quality parameters was investigated. Both purée and extract containing products had a pleasant taste with a vegetable note and uniform consistency. Sulforaphane content in 200 g beverage servings was (23.5 ± 2.1) mg and (29.5 ± 0.5) mg (extract), both values approximately one tenth of therapeutic dose estimates, which is enough for cancer preventive purposes.

FEATURES OF BRASSICA RAPA'S GROWTH AND DEVELOPMENT, DEPENDING ON THE TERRITORY OF SOWING THE SEED

In order to study the effect of the time of sowing seeds on the passage of morphogenesis and productivity of rapeseed, the scheme included experiments where the seeds were sown in I, II, III in April, I and II in May. The experiment used varieties of Golden Ball, Purpurleopop, Purpurov and Geisha, and control was the variant in which the seeds of the Golden Ball varieties were sown in the second decade of April with a row spacing of 45 cm. laboratory - to determine the total yield; statistical - to establish the reliability of the investigated factors. Seed germination analysis used in the experiment ranged from 78.9% to 81.1% on average. The highest indicator of seed germination was characterized by the Purpulepop variety, where the studied value was 83.2%, which was dominated by the seed germination of the control variant by 2.1%. In the early stages of sowing seeds, the period of seedling formation was shorter. Seeding of seeds in the first two decades of April on the surface of the soil was observed for 8 days. The short sprouting period was characterized by all varieties of turnips. As a result of sowing turnip seeds at a later date, namely in the third decade of April - the first and second decade of May and the setting of a higher soil temperature, the period of germination was extended and ranged from 8 to 10 days. By using the term of sowing seeds I-II decade of April, the short interphase period was characterized by Purpleupop and Purpurova varieties, where the specified period was only 22 days. The sowing of turnip seeds at a later date ensured the formation of an interphase period of "seedlings - leaf rosette" in 23-25 days except Purpulopop variety. The interphase period "leaf rosette - the beginning of rooting" and "the beginning of rooting - technical maturity" determined the benefits of early seeding, namely in the first decade of April on varieties Purpulopop and Purpurov.The short vegetation period was characterized by the Golden Ball plants for sowing seeds in the first and third decades of April and the first of May. During the specified seeding period the duration of the growing season was only 40 days. A longer vegetation period was characterized by plants of the Geisha variety for sowing seeds in the first two decades of April. As a result of the use of the researched elements of technology to grow turnips in open soil, the total yield varied from 11.0 t / ha to 24.0 t / ha. The most productive is the first sowing of rapeseed, where its value ranged from 20.6 t / ha to 22.7 t / ha. At the same time, when sowing seeds in the first decade of April, the yield of turnip varieties Purpulepop was the highest and was 22.7 t / ha, or the increase was 2.4 t / ha.

The Sun Ray as a Tool to Design an Architectural Form

The regularities of constructing crucial architectural forms are shown based on the architecture of Ancient Egypt, Western Europe, and Russia: obelisks, pyramids, statues, tents, and spires. It is shown that the source of projection for these and some other architectural forms was the Sun 1 or its image in the shape of a golden ball. The sun ray is serving as a tool for solar elevation.

A Hybrid Meta heuristic Algorithm for the Balanced Line Production under Uncertainty

This study proposes a hybrid Golden Ball Algorithm for solving a balanced line production for a garment firm in Thailand. At present, production lines are those in which the timing of the job movement between stations is coordinated in such a way that all of the jobs are indexed simultaneously via some heuristic sequencing or dispatching rules. This research studies the balanced line production problem with some stochastic patterns, and develops a Golden Ball Algorithm or GBA and its variants to solve the problem. To assess the effectiveness of the proposed hybrid algorithm, a computational study is conducted for both deterministic and stochastic patterns of the problem. The comparisons are made for two different levels of processing times and due date. It can be concluded that the variant HGBA2 of the algorithm by adjusting answers of the successor function on both custom training and successor phases, is slightly more effective than the other hybrid approaches in terms of quality of solutions under uncertainty.

Efficient Golden-Ball Algorithm Based Clustering to solve the Multi-Depot VRP With Time Windows

In this article, the authors propose a decision support system which aims to optimize the classical Capacitated Vehicle Routing Problem by considering the existence of multiple available depots and a time window which must not be violated, that they call the Multi-Depot Vehicle Routing Problem with Time Window (MDVRPTW), and with respecting a set of criteria including: schedules requests from clients, the capacity of vehicles. The authors solve this problem by proposing a recently published technique based on soccer concepts, called Golden Ball (GB), with different solution representation from the original one, this technique was designed to solve combinatorial optimization problems, and by embedding a clustering algorithm. Computational results have shown that the approach produces acceptable quality solutions compared to the best previous results in similar problem in terms of generated solutions and processing time. Experimental results prove that the proposed Golden Ball algorithm is efficient and effective to solve the MDVRPTW problem.