Quantitative Evaluation Criteria Research Articles

An Evaluation Method of Dental Treatment Quality Combined with Deep Learning and Multi-index Decomposition

ABSTRACT Dentists judge that the quality of dental treatment for each patient is very time-consuming and inefficient, lacks quantitative evaluation criteria, and is easy to cause errors. At the same time, the traditional method of extracting tooth and root canal image features based on experience is difficult to accurately extract the tooth area and root canal filling area, resulting in low accuracy of tooth and root canal segmentation, which in turn affects the accuracy of tooth treatment quality evaluation. In this paper, a deep learning convolutional neural network is used to segment the root canal filling area, tooth boundary, and the boundary between tooth and soft tissue for the real patient ‘s root canal treatment and filling image. Finally, the segmented image is quantitatively evaluated according to the multi-evaluation index of professional doctors. The experimental results show that the intelligent evaluation method of dental treatment quality combined with deep learning and multi-index decomposition proposed in this paper not only unifies the evaluation criteria of dental treatment quality but also the therapeutic effect of quantitative scoring can effectively improve the work efficiency of doctors, which has reference significance for the application of artificial intelligence in the medical field.

Wind Shear Operation-Based Competency Assessment Model for Civil Aviation Pilots

Undesirable meteorological conditions are typical aviation flight safety threats. Although most meteorological radar and flight augmentation computers have avionic system wind shear alarms, the preferred approach is that pilots avoid unsafe wind shear events. Therefore, effective pilot competency evaluations are needed to assess pilots’ abilities to deal with these events. This study developed a wind shear operation competency model that includes observable behavior indicators, sub-task decomposition, and competency check items. An adapted competency model and a quantitative data-driven competency evaluation criteria optimization method were then developed using three-dimensional competency feature modeling, after which wind shear simulation flight training data were used to verify the effectiveness of the proposed method. The competency assessment grades were significantly correlated with the results from experienced examiners with a 93.33% evaluation accuracy. The proposed quantitative data-driven competency assessment method can provide effective pilot competency assessments for a range of aviation meteorological threats.

Evaluation method for electromagnetic interference complexity of high voltage switch based on feature extraction and GCC‐GRU network

AbstractWhen some new‐type sensors are subjected electromagnetic interference (EMI), the traditional standard can no longer serve as the guidance for their EMI protection. Therefore, it is necessary to evaluate the complexity of the new sensing equipment's suffering from electromagnetic interference. A hybrid method of feature extraction and complexity evaluation of Electromagnetic Interference signals based on generalised correntropy criterion (GCC) is proposed. First, a variational mode decomposition algorithm for adaptive extraction of decomposed signals is constructed using GCC, and Generalised S‐transform is used for processing and reorganisation. Then, according to the time‐frequency space model, a new quantitative evaluation criterion interference factor is proposed, which overcomes the shortcomings of the traditional qualitative classification and the inability to solve the cross classification of indicators. Then, the Gated Recurrent Unit is introduced, and the GCC‐GRU evaluation model with GCC as the loss function is derived. The authors conduct EMI tests and measured signal evaluation with Medium Voltage and High Voltage switches, and the results show that the method proposed is correct and effective.

Multi-Frequency GPR Data Fusion through a Joint Sliding Window and Wavelet Transform-Weighting Method for Top-Coal Structure Detection

Top-coal structure detection is an important basis for realizing effective mining in fully mechanized cave faces. However, the top-coal structure is very complex and often contains multi-layer gangues, which seriously influence the level of effective mining. For these reasons, this paper proposes a novel multi-frequency ground-penetrating radar (GPR) data-fusing method through a joint sliding window and wavelet transform weighting method to accurately detect the top-coal structure. It possesses the advantages of both high resolution and great detection depth, and it can also integrate multi-frequency GPR data into one composite profile to interpret the internal structure information of top coal in detail. The detection procedure is implemented following several steps: First of all, the multi-frequency GPR data are preprocessed and aligned through a band-pass filter and a zero offset elimination method to establish their spatial correspondences. Secondly, the proposed method is used to determine the time-varying weight values of each frequency GPR signal according to the wavelet energy proportion within the sliding window; also, the edge detection algorithm is introduced to improve the fusion efficiency of the wavelet transform so as to realize the effective fusion of the multi-frequency GPR data. Thirdly, a reflection intensity model of multi-frequency GPR signals traveling in the top-coal is established by using the stratified identification method, and then, the detailed top-coal structure can be inversely interpreted. Finally, the quantitative evaluation criteria, information entropy (IE), space–frequency (SF) and Laplacian gradient (LG), are used to evaluate the multi-frequency GPR data fusion’s effectiveness in laboratory and field environments. The experimental results show that, compared with the genetic, time-varying and wavelet transform fusion method, the fusion performance of the presented method possesses higher values in the IE, SF and LG evaluation criteria, and it also has both the merits of high resolution and great detection depth.

Mechanisms and progress in the application of traditional acupuncture methods for the treatment of lumbar disc herniation

This paper summarizes the operational methods of nine acupuncture techniques recorded in the Ling Shu Guan Zhen and the mechanisms of special acupuncture techniques in the treatment of lumbar disc herniation over the past two decades. The techniques include the left and right crossing acupuncture method, local multi-needle acupuncture method, bone-piercing method, and tendon-piercing method. An overview of the types of lumbar disc herniation suitable for each acupuncture technique is provided, offering a theoretical reference for selecting appropriate acupuncture techniques in clinical treatment. However, current research lacks an exploration of the differential efficacy mechanisms among different acupuncture techniques for treating lumbar disc herniation. Issues such as the absence of standardized quantitative evaluation criteria, limited sample sizes, and a lack of long-term efficacy tracking still need improvement in future research.

Advanced methods for the detection of measurement outliers in fibre optic strain measurements for non-destructive monitoring of the structural health of composite over-wrapped pressure vessels of type-IV

To analyse the applicability of fibre optic measurements as a measurement method for structural health monitoring, fibre-optic sensors are placed on the vessel surface. The influence of the surface profile of the vessel on the measurement result is analysed by correlating the 3D scanned surface and measurement results. One outcome is that the measurement is substantially influenced by the surface topography. The surface height can be directly correlated to the strain magnitude, which is also verified by analytical calculations. Outliers and invalid values can be traced back to surface-related influences on the sensor fibre. For the outlier detection, a novel method is presented, which is based on quantitative evaluation criteria and inductive reasoning and enables transient cycle- by-cycle outlier detection adapted to the load case. Based on the results an estimate for the expanded measurement uncertainty is given for of the measurement chain consisting of vessel, adhesive and sensor fibre.

EXPERIMENTAL STUDIES OF THE DISPENSER OF THE SEEDING APPARATUS OF THE SELECTION SEEDER OF SMALL SEED CULTURES

A mock-up sample of the dispenser of the seeding device of the selection seeder as part of the laboratory stand was developed. The MG995 servo drive is used as a drive for the seeding machine dispenser. The experimental stand includes a conveyor belt that simulates the process of moving a planter. The drive of the conveyor belt is a stepper motor SY42STH38-1684A. The numerical modeling factors are the diameter of the seed Dμ (0.001–0.003 m), the angle of rotation of the flap α (0.3489–0.8028 rad), the time interval when the flap is open or closed Δt (0.2–0.4 s), the speed movement of the conveyor belt (planter) V (1–4 m/s). Quantitative evaluation criterion is seed sowing rate N. Qualitative evaluation criterion is sowing accuracy δ. As a result of experimental studies of the dosing device of the selection planter of small-seeded crops, the dependences of the seed sowing rate N and sowing accuracy δN on the average effective seed diameter Dμ, the flap rotation angle α, the time interval when the flap is open or closed Δt and the movement speed of the planter V for three options were established the shape of the holes. A visual and statistical comparison of theoretical and experimental dependences testifies to the adequacy of the obtained theoretical models and the reliability of the obtained experimental regularities. It was established that the accuracy of seeding δN for the 1st version of the hole (triangle) of the metering unit of the sowing device is in the range of 78.0–99.9%, for the 2nd version (semicircle) the range is 71.1–98.3%, for the 3rd version (rectangle) range 67.3–97.4%. Therefore, taking into account the theoretical conclusion and the obtained experimental data, in further studies we accept the 1st version of the holes (triangular).

Sustainable Evaluation of Major Third-Party Logistics Providers: A Framework of an MCDM-Based Entropy Objective Weighting Method

This study aims to efficiently assist decision makers in evaluating global third-party logistics (3PL) providers from the perspectives of economic, social, and environmental sustainability and explore the determinants of the 3PL providers’ performance. In doing so, an integrated framework for an MCDM-based entropy objective weighting method is proposed for the first time in a logistics industry assessment. In the first stage, the entropy method defines the weight of the decision criteria based on real data collected from the top 15 global 3PL providers. This study lists the prominent quantitative evaluation criteria, taking into consideration the sustainability perspective. The advantage of the entropy method is that it reduces the subjective impact of decision makers and increases objectivity. In the second stage, the measurement of alternatives and ranking according to compromise solution (MARCOS) method is used to rank the 3PL providers according to their performance on the basis of these criteria. Sensitivity analysis and comparative analysis are implemented to validate the results. The current research work is devoted to the emerging research topic of sustainable development in the logistics industry and supply chain management. The proposed model identifies key performance indicators in the logistics industry and determines the most efficient 3PL providers. Consequently, the results show that the carbon dioxide emissions (20.50%) factor is the most important criterion for the competitiveness of global logistics companies. The results of this study can help inefficient 3PL providers make strategic decisions to improve their performance. However, this study only focuses on 15 companies due to a lack of data. The integration of these two techniques provides a novel way to evaluate global 3PL providers which has not been addressed in the logistics industry to date and as such remains a gap that needs to be investigated.

An optimal adaptive S-transform time-frequency space model for electromagnetic interference complexity evaluation

The issue of significant amplitude shifting with frequency in the evaluation of electromagnetic interference complexity using the S-transform can result in inaccurate extraction of energy occupancy evaluation parameters. This paper proposes a method of electromagnetic environment complexity evaluation based on the optimal adaptive S-transform (OAST) time-frequency space model. Firstly, the flexible adjustment of the window width of the S-transform window function is achieved by introducing adaptive parameters, so as to suppress the large migration of the amplitude characteristics with the signal frequency. Then, the calculation formulae for the evaluation parameters of time occupation, frequency occupation and energy occupation based on OAST are derived, and the OAST time-frequency spatial evaluation model is established; Finally, the qualitative and quantitative evaluation criteria of subjective and objective complexity based on the OAST time-frequency spatial model are analyzed and determined, overcoming the limitations of the independent grading of the traditional electromagnetic interference complexity evaluation parameters. Simulation and experimental results show that OAST can accurately extract the time-frequency energy occupation parameters and the feature parameters in the time-frequency domain are more accurate; the OAST time-frequency spatial model can evaluate the signal complexity level more accurately, and the evaluation experiments verify the correctness of the proposed method.

Hesitant triangular fuzzy FlowSort method: the multi-criteria decision-making problems

Multi-criteria sorting problems have gained significant importance across various fields. However, when experts express their opinions using linguistic terms and quantitative evaluation criteria are not feasible, the fuzzy set theory proves to be a suitable framework. Moreover, in such scenarios, the use of hesitant fuzzy sets becomes necessary because each criterion might have multiple values compared with other alternatives. This paper introduces a novel method called Hesitant Triangular Fuzzy Sorting (HTFFS), which is a variation of the fuzzy FlowSort method based on the preference ranking organisation method for enrichment evaluation (PROMETHEE). The HTFFS method incorporates the theory of fuzzy sets and establishes theoretical foundations for calculating the degree of superiority of each alternative over others. This calculation uses mathematical operators specifically designed for uncertain fuzzy sets and uncertain triangular fuzzy numbers. To demonstrate the effectiveness and practicality of the proposed HTFFS method, two numerical examples are presented. The results obtained from these examples showcase the applicability and validity of the HTFFS method in handling multi-criteria sorting problems.

Evaluation of the turbulent hot jet flame characteristics for achieving high thermal efficiency of hybrid engine

Turbulent jet ignition with active pre-chamber (APC) could enhance the ultra-lean combustion stability thus improving the engine's thermal efficiency. Different APCs structures are analyzed in previous studies, but the lack of quantitative evaluation criteria makes it difficult to optimize the APC under various engine conditions. This paper aims to investigate the characteristic of APC hot jets and their effects on ignition capability and engine combustion performance from perspectives of jet velocity, temperature, turbulent kinetic energy (TKE), and turbulent intensity. The quantitatively evaluate method of hot jet activity based on the key intermediate species during the chemical reactions was proposed. Different APC jet flames and corresponding engine main chamber (MC) combustion performance were discussed by adjusting the APC nozzle diameter and number. The result showed that the jet velocity in a certain range of 450 to 700 m/s has a positive effect on igniting the ultra-lean mixture inside MC. The jet velocity mainly affects the ignition position of jet flame in MC, a higher jet velocity induces the ignition to occur near the cylinder wall and increases the thermal diffusion and heat losses, leading to the lower ignition ability. The jet temperature shows a relatively lower effect on igniting the ultra-lean mixture as the maximum jet flame temperature is over 2250 K. The jet TKE and velocity exhibit a strong correlation in engine performance. The jet turbulence intensity rather than jet TKE strongly influences igniting the ultra-lean mixture. The jet turbulence intensity in the range of 0.025 to 0.035 is beneficial to ignition ability and engine combustion performance. The 4-nozzle APC produces a relatively high jet activity. It’s confirmed that the jet activity higher than 0.055 is sufficient for igniting the ultra-lean mixture. The 4-nozzle APCs can achieve higher engine-indicated thermal efficiency (ITE) as compared to 6-nozzle APCs. The peak ITE of 51.6% is achieved by the 4-nozzle APC with an orifice diameter of 1.8 mm that meets all the good jet characteristics that can produce strong ignition capability.

Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images

Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons. The virus was swiftly gone viral around the world and a lot of fatalities and cases growing were recorded on a daily basis. CXR can be used to monitor the effects of COVID-19 on lung tissue. This study examines a comparison analysis of k-nearest neighbors (KNN), Extreme Gradient Boosting (XGboost), and Support-Vector Machine (SVM) are some classification approaches for feature selection in this domain using The Moth-Flame Optimization algorithm (MFO), The Grey Wolf Optimizer algorithm (GWO), and The Glowworm Swarm Optimization algorithm (GSO). For this study, researchers employed a data set consisting of two sets as follows: 9,544 2D X-ray images, which were classified into two sets utilizing validated tests: 5,500 images of healthy lungs and 4,044 images of lungs with COVID-19. The second set includes 800 images, 400 of healthy lungs and 400 of lungs affected with COVID-19. Each image has been resized to 200x200 pixels. Precision, recall, and the F1-score were among the quantitative evaluation criteria used in this study.

A grey ordinal priority approach for healthcare waste disposal location selection

PurposeIncreasing public consciousness and demand for sustainable environment make selection of a safe location for effective disposal of healthcare waste (HCW) a challenging issue. This problem becomes more complicated due to involvement of multiple decision makers having varying knowledge and interest, conflicting quantitative and qualitative evaluation criteria, and presence of several alternative locations.Design/methodology/approachTo efficiently resolve the problem, the past researchers have already coupled different multi-criteria decision-making tools with uncertainty models and criteria weight measurement techniques, which are time-consuming and highly computationally complex. Based on involvement of a group of experts expressing their opinions with respect to relative importance of criteria and performance of alternative locations against each criterion, this paper proposes application of ordinal priority approach (OPA) integrated with grey numbers to solve an HCW disposal location selection problem.FindingsThe grey OPA can simultaneously estimate weights of the experts, criteria and locations relieving the decision makers from complicated computational steps. The potentiality of grey OPA in solving an HCW disposal location selection problem is demonstrated here using an illustrative example consisting of three experts, six criteria and four alternative locations.Originality/valueThe derived results show that it can be employed to deal with real-time HCW disposal location selection problems in uncertain environment providing acceptable and robust decisions. It relieves the experts from pair-wise comparisons of criteria, normalization of data, identification of ideal and anti-ideal solutions, aggregation of information and so on, while arriving at the most consistent decision with minimum computational effort.

Research on Safety Evaluation and System Development of Tunnel Lining Based on Set Pair Analysis

Considering the importance of lining thickness in lining safety, and realizing the synchronization of safety evaluation and information development, this paper combines the methods of literature research and field investigation, focuses on six influencing factors, such as the deterioration of lining materials, the deformation of lining and the lack of tunnel clearance, et al. An evaluation index system of structural safety classification is established, and then substantiates each index and defines its quantitative or qualitative evaluation criteria. Through the normalization processing, the state of the evaluation index can be characterized by the normalized value. Analysing the characteristics, structure, relationship, trend and the mode of their mutual connection between the indexes by set pair analysis method, the calculation formula of the connection degree is obtained, and then the set pair potential vector is obtained. According to the principle of maximum set pair potential, the safety evaluation of lining structure is divided into five levels: safe, safer, less safe, unsafe and extremely unsafe. With the help of App Designer tool in MATLAB software, a program suitable for lining safety evaluation is designed and developed independently. Combined with a tunnel project in Chongqing, the above method is used to judge the lining safety of the tunnel project in order to provide a quick way for tunnel safety evaluation.

A Novel Crowdsourcing Task Recommendation Method Considering Workers’ Fuzzy Expectations: A Case of ZBJ.COM

Crowdsourcing recommendation is necessary to surmount information overload and assist workers to identify tasks of interest efficiently. However, existing studies mainly concentrate on investigating workers’ qualifications or requirements, neglecting their fuzzy expectations and psychological behavior. Besides, workers can only passively accept the results and do not have any right to change them even if they are not satisfactory. As workers will pay different attention to task aspects, we regard the crowdsourcing recommendation as a multi-criteria decision-making (MCDM) problem. In this paper, we propose an MCDM-based method for automated and interactive crowdsourcing task recommendations while comprehensively considering workers’ fuzzy expectations and psychological behavior. Given a large volume of available tasks on a crowdsourcing platform, the requirement of massive human efforts in traditional MCDM is not applicable in such situation. Therefore, we formulate a set of quantitative task evaluation criteria for automated task assessments based on the attributes that have the most impact on workers’ participation behavior. Further, to capture workers’ fuzziness in expectations, an intuitionistic fuzzy 2-tuple linguistic (IF2L) term is introduced, which are further leveraged as reference points to evaluate their “gains” and “losses” based on the prospect theory. Finally, the D-S evidence theory is adopted to gather workers’ uncertain prospect values. A case of ZBJ.COM, a popular crowdsourcing platform in China, shows that the proposed method is efficient and effective in recommending suitable and personalized tasks to workers.

Modified quantitative and volumetric response evaluation criteria for patients with hepatocellular carcinoma after transarterial chemoembolization.

This study aimed to investigate the cutoff value of quantitative and volumetric response evaluation criteria for patients with hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE) and compare the performance of the modified criteria to one-dimensional criteria in survival prediction. A retrospective single-center study was performed for treatment-naive patients with HCC who underwent initial TACE between June 2015 and June 2019. Treatment response assessment was performed after the first observation by contrast CT or MRI, with the measurement of diameters by modified Response Evaluation Criteria in Solid Tumors (mRECIST) and volumes by quantitative European Association for Study of the Liver (qEASL). Overall survival (OS) was the primary endpoint of this study. The new cutoff value for volumetric response evaluation criteria was created using restricted cubic splines. The performance of modified qEASL (mqEASL, with the new cutoff value) and mRECIST on survival prediction was compared by Cox regression models in internal and external validation. A total of 129 patients (mean age, 60 years ± 11 [standard deviation]; 111 men) were included and divided into training (n=90) and validation (n=39) cohorts. The cutoff value for the viable volume reduction was set at 57.0%. The mqEASL enabled separation of non-responders and responders in terms of median OS (p<0.001), 11.2 months (95% CI, 8.5-17.2 months) vs. 31.5 months (95% CI, 25.5-44.0 months). Two multivariate models were developed with independent prognostic factors (tumor response, metastasis, portal vein tumor thrombus, and subsequent treatment) to predict OS. Model 2 (for mqEASL) had a greater Harrel's C index, higher time-dependent area under the receiving operator characteristic curve (AUROC), and more precise calibration on 6-month survival rates than Model 1 (for mRECIST). With the modified cutoff value, the quantitative and volumetric response of HCC patients to TACE becomes a precise predictor of overall survival. Further studies are needed to verify this modification before application in clinical practice.

A novel multilevel decision-making evaluation approach for the renewable energy heating systems: A case study in China

Renewable energy (RE) sources are important alternatives to mitigate the energy crisis and achieve sustainable development. Appropriate selection of RE system solutions is extremely crucial. Selection of the best RE technology requires the consideration of conflicting qualitative and quantitative evaluation criteria. Many evaluation criteria are judged with subjectivity and uncertainty. However, the description of uncertainty in the evaluation process remains a large research gap. Therefore, a novel combined evaluation method is developed to describe and visualize the uncertainty in the assessment process. The proposed evaluation method is tested for RE heating system selection. The RE systems are evaluated based on five dimensions and 15 evaluation indicators. This multidimensional indicator framework not only includes the three basic evaluation groups of energy, economy, and environment, but also extends to the performance of technology and policy. The combined weights of the evaluation indicators consist of objective weights and subjective weights. The objective weights are obtained by the Criteria Importance Through Intercriteria Correlation (CRITIC) method and subjective weights are calculated by the improved Fuzzy Analytic Hierarchy Process (FAHP). The set pair analysis (SPA) is introduced to assess the performance of different RE systems. It considers the uncertainty of indicator performance. A novel approach to visualizing the fuzziness of SPA evaluation is developed using the cloud model. Finally, the RE system ranking calculated by the proposed method is performed. The originality of this work is offering a promising method for RE selection and clarifying the degree of ambiguity in the evaluation process. It helps decision makers have an exact idea about the accuracy of the evaluation. It provides insights into multi-objective decision-making problems.

Methods of Indirect Identification in the Hand of a Crisis Manager in the Context of Sociological Aspects

This paper aims to describe the basic methodological approaches in experimental wounding ballistics, which are methods of indirect identification, especially with an emphasis on the sociological content and perspectives of current trends in security management. The outputs and conclusions presented in the paper result from a thorough analysis of threats and security risks identified in the research work in the context of the IGA project No. 007DTI / 2019 realized at DTI University in Dubnica nad Váhom, arising from the actual security situation in society using conventional weapons systems against human beings, and from the analyze of existing quantitative evaluation criteria for the bullets wounding potential. The main theoretical and experimental output is the conceptual proposal of own bullets wounding potential evaluation criterion.

Selection of non-financial sustainability indicators as key elements for multi-criteria analysis of hotel chains

Nowadays, online information provided by corporate websites has a great impact on the hotel industry performance. According to existing studies, it is very likely that customers' and investors' decisions may change after consulting these portals. The environmental commitment of hotel companies is usually demonstrated to stakeholders by obtaining environmental quality certifications and eco-labels issued by specialised entities in compliance with certain requirements. However, the question of how to use the sustainable indicators that are usually scattered on the web or in company reports is a problem that requires further research. The main objective of this study is to develop a robust and reliable model to assess the sustainability of hotel chains based on the information gathered from their websites and corporate reports. A literature review is carried out and specialists are consulted to determine the critical factors that affect hotel sustainability. Once the criteria based on non-financial indicators have been chosen, they are organised in a hierarchy according to their orientation. To achieve the objective of the study, a hybrid model is proposed that includes two multi-criteria decision-making approaches, namely the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. AHP is used to weight the criteria, and the ranking of the alternatives is provided through TOPSIS. Subsequently, a sensitivity analysis is performed to determine the critical indicators. Finally, a numerical example is carried out with a case study of the largest Spanish hotel chains to illustrate the function and applicability of the proposed method. With the results obtained, it has been possible to establish a ranking or selection of hotel chains for the case study, since the hybrid AHP-TOPSIS method provides reliable and robust results for any qualitative or quantitative evaluation criterion, which is of great interest for the different actors involved.

The Selection of Skylight Type for a Certain Building Using Evaluation Criteria and the Multi-Criteria Decision-Making Method

The article is focused on the selection of the rational skylight from the examined alternatives using quantitative and qualitative evaluation criteria, which are based on skylight performance and the multi-criteria decision-making method. A non-residential building, namely, a car service shop, was chosen for the research in order to offer good lighting in the large hall where the car repair work is performed every workday. Three alternatives of skylights with glazing material of spherical shape or dome were chosen for the study, skylight domes, longitudinal skylights, and tubular skylights, whose selection was based on the technical parameters of the product and the calculated amount of natural light entering through three different types of skylights. The skylight alternatives were evaluated according to seven criteria whose priority ranking and importance were determined by the survey questionnaire, while the theoretical and complex importance was determined using the Entropy Method. The most rational type of skylight was determined by the TOPSIS method. The analysis based on the offered method showed that skylight domes are a rational solution for the choice of skylight type for the tested building. The main criterion for choosing the roof daylighting system according to the survey was heat transfer coefficient, while skylight cost and installation cost were the criteria chosen by Entropy Method. In both cases, when alternative solutions were compared using the theoretical and complex importance of evaluation criteria, the most rational type of skylight selected using the TOPSIS method was the same alternative, namely the skylight dome.