Computational optimization of housing complexes forms to enhance energy efficiency

This study aimed to consider the field of energy saving in architectural design utilizing computer analysis and calculation. In this analysis, architecture design with an approach to optimizing energy consumption in the design of individual units, complex plan sites, and apartment sets using a computer was studied. Parameters affecting this research include the geometry of units, the arrangement and location relationship of buildings, and the form and height of apartment units. Different plans were produced by utilizing the initial plan of the designer and changing some aspects of it approved by the architectural design using the parametric modeling technique. Utilizing similar logic and a shift in the arrangement of buildings on the site, a variety of options were produced. By selecting existing and pre-designed plans, the optimal form was produced by computer. After computer-simulating each option, the energy analysis process was started for each building design. In the optimization process for each of the three designs, a genetic algorithm was used to achieve the optimal solution. After accomplishing the various stages of optimization, the final option compared with the initial design had reductions in energy consumption of 21% in plan design, 2% in site plan design, and 26% in apartment units form design. It should be noted that the processes of simulation and optimization were performed in the context of a continuous algorithm and by utilizing parametric tools that reduced the duration of this process

Implementation of EU energy policy priorities in the Baltic Sea Region countries: Sustainability assessment based on neutrosophic MULTIMOORA method

The European Union (EU) has set ambitious goals for climate change and energy in its pursued policies (20% of renewable energy until 2020, 27% until 2030, and the aim to become the global leader in energy produced by renewable energy sources). Even more ambitious goals are established in the strategy of Energy 2050. Today European energy policy is oriented towards energy security, expansion of energy markets, energy efficiency, decarbonisation, and scientific research and innovations

M-generalised q-neutrosophic extension of CoCoSo method

Nowadays fuzzy approaches gain popularity to model multi-criteria decision making (MCDM) problems emerging in real-life applications. Modern modelling trends in this field include evaluation of the criteria information uncertainty and vagueness. Traditional neutrosophic sets are considered as the effective tool to express uncertainty of the information. However, in some cases, it cannot cover all recently proposed cases of the fuzzy sets. The m-generalized q-neutrosophic sets (mGqNNs) can effectively deal with this situation. The novel MCDM methodology CoCoSomGqNN is presented in this paper. An illustrative example presents the analysis of the effectiveness of different retrofit strategy selection decisions for the application in the civil engineering industry

Application of Sustainability Principles for Harsh Environment Exploration by Autonomous Robot

Currently, the European Union (EU) is focusing on a large-scale campaign dedicated to developing a competitive circular economy and expanding the single digital market. One of the main goals of this campaign is the implementation of the sustainability principles in the development and deployment cycle of the new generation technologies. This paper focuses on the fast-growing field of autonomous mobile robots and the harsh environment exploration problem. Currently, most state-of-the-art navigation methods are utilising the idea of evaluating candidate observation locations by combining different task-related criteria. However, these map building solutions are often designed for operating in near-perfect environments, neglecting such factors as the danger to the robot. In this paper, a new strategy that aims to address the safety and re-usability of the autonomous mobile agent by implementing the economic sustainability principles is proposed. A novel multi-criteria decision-making method of Weighted Aggregated Sum Product Assessment—Single-Valued Neutrosophic Sets, namely WASPAS-SVNS, and the weight selection method of Step-Wise Weights Assessment Ratio Analysis (SWARA) are applied to model a dynamic decision-making system. The experimental evaluation of the proposed strategy shows that increased survivability of the autonomous agent can be observed. Compared to the greedy baseline strategy, the proposed method forms the movement path which orients the autonomous agent away from dangerous obstacles

Procedural Video Game Scene Generation by Genetic and Neutrosophic WASPAS Algorithms

The demand for automated game development assistance tools can be fulfilled by computational creativity algorithms. The procedural generation is one of the topics for creative content development. The main procedural generation challenge for game level layout is how to create a diverse set of levels that could match a human-crafted game scene. Our game scene layouts are created randomly and then sculpted using a genetic algorithm. To address the issue of fitness calculation with conflicting criteria, we use weighted aggregated sum product assessment (WASPAS) in a single-valued neutrosophic set environment (SVNS) that models the indeterminacy with truth, intermediacy, and falsehood memberships. Results are presented as an encoded game object grid where each game object type has a specific function. The algorithm creates a diverse set of game scene layouts by combining game rules validation and aesthetic principles. It successfully creates functional aesthetic patterns without specifically defining the shapes of the combination of games’ objects

Adaptive Autonomous Robot Navigation by Neutrosophic WASPAS Extensions

In this research, a novel adaptive frontier-assessment-based environment exploration strategy for search and rescue (SAR) robots is presented. Two neutrosophic WASPAS multi-criteria decision-making (MCDM) method extensions that provide the tools for addressing the inaccurate input data characteristics are applied to measure the utilities of the candidate frontiers. Namely, the WASPAS method built under the interval-valued neutrosophic set environment (WASPAS-IVNS) and the WASPAS method built under the m-generalised q-neutrosophic set environment (WASPAS-mGqNS). The indeterminacy component of the neutrosophic set can be considered as the axis of symmetry, and neutrosophic truth and falsity membership functions are asymmetric. As these three components of the neutrosophic set are independent, one can model the input data characteristics applied in the candidate frontier assessment process, while also taking into consideration uncertain or inaccurate input data obtained by the autonomous robot sensors. The performed experiments indicate that the proposed adaptive environment exploration strategy provides better results when compared to the baseline greedy environment exploration strategies

Qualitative Rating of Lossy Compression for Aerial Imagery by Neutrosophic WASPAS Method

The monitoring and management of consistently changing landscape patterns are accomplished through a large amount of remote sensing data using satellite images and aerial photography that requires lossy compression for effective storage and transmission. Lossy compression brings the necessity to evaluate the image quality to preserve the important and detailed visual features of the data. We proposed and verified a weighted combination of qualitative parameters for the multi-criteria decision-making (MCDM) framework to evaluate the quality of the compressed aerial images. The aerial imagery of different contents and resolutions was tested using the transform-based lossy compression algorithms. We formulated an MCDM problem dedicated to the rating of lossy compression algorithms, governed by the set of qualitative parameters of the images and visually acceptable lossy compression ratios. We performed the lossy compression algorithms’ ranking with different compression ratios by their suitability for the aerial images using the neutrosophic weighted aggregated sum product assessment (WASPAS) method. The novelty of our methodology is the use of a weighted combination of different qualitative parameters for lossy compression estimation to get a more precise evaluation of the effect of lossy compression on the image content. Our methodology includes means of solving different subtasks, either by altering the weights or the set of aspects