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Given its widespread potential and technological advancements, it is critical to use the greatest amount of wind power in reaching the 100% renewable energy target in power grids. SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis is frequently used to evaluate alternative strategies in multi-criteria decision issues. This paper employs a hybrid Fuzzy Analytic Network Process (FANP) approach based on SWOT to assess the future development of wind power capacities in Turkey in light of the sectoral effects of the Covid-19 outbreak in 2020. To validate the proposed approach, the results are compared to the results of the SWOT-based Analytic Network Process (ANP), Analytic Hierarchy Process (AHP), and fuzzy AHP (FAHP). According to the findings, "Development of domestic and efficient technologies (ST1)" and "Sustaining support mechanisms in investments and technological research (SO2)" are the best alternative strategies in all analysis models. While the priority ranks of other alternative strategies are the same in AHP and FAHP hierarchical techniques, FANP differs from ANP when the linguistic assessment process is taken into account. This study proposes long-term strategies for increasing wind power capacity and sector sustainability, and it demonstrates that FANP could be an appropriate approach for prioritizing these strategies in current scenarios. [ABSTRACT FROM AUTHOR]

This paper aims to determine the suitable places for a radioactive waste repository in Peninsular Malaysia to implement a permanent disposal facility for disposal sealed radioactive sources (DSRS). The sole Malaysia interim waste storage that stores a large proportion of DSRS was expected to be occupied by 2025 fully. Currently, the nation's licensing board promoted the borehole disposal facility to resolve the full capacity dilemma. The potential sites were determined by the geographical information system (GIS) based Weight Linear Combination (WLC) analysis, integrating the improved Analysis Hierarchical Process (improved AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) approaches. The sensitivity analysis was applied to identify the main contributing factors for corresponding Peninsular Malaysia selection. Ten parametric criteria and three exclusion criteria are applied to assess the potential areas and screen out the unfavorable regions, respectively. Results indicated the final composite map presents 435 areas of very high suitability class with 17.5% coverage from the total suitability class. The top 5 largest candidates with high potentiality are Jerantut & Ulu Lepar, Bandar Tun Razak, Pertang & Simpang, Pertang, Tanjung Ipoh, and Labis, where come from three provinces: Pahang, Negeri Sembilan and Johor. By TOPSIS model, the ranks for these five candidates are Jerantut & Ulu Lepar, Bandar Tun Razak, Tanjung Ipoh, Labis and Simpang Pertang. The model revealed that the suitability ranks is proportional to its area sizes in the approximate values of criteria. The three main contributing factors in Peninsular Malaysia are hydrogeology, seismicity and lithology, which are strongly recommended to involve in other corresponding site selection project. • Top five candidates for radioactive waste disposal site in Malaysia are Jerantut & Ulu Lepar, Bandar Tun Razak, Tanjung Ipoh, Labis and Simpang Pertang. • Three main contributing factors for site selection in Malaysia are hydrogeology, seismicity and lithology. • The suitability index rank is proportional to the area sizes in the consideration of area factor. [ABSTRACT FROM AUTHOR]

The European spruce bark beetle ' Ips typographus L.' is the most serious disturbance agent for European forests. The complex interactions of many influencing factors need to be integrated into a model-based decision-support system to reduce the potential loss of forests. This paper compares two methodological approaches for spatially-explicit prediction of the predisposition for bark beetle infestations. The fuzzy analytic hierarchy process and the Bayesian belief networks were used in combination with a geographical information system to manage uncertainties. Using available data resources, the two approaches were evaluated to produce robust results for forest practitioners and to support measures to minimize the spread of bark beetles. The findings revealed that nearly 32% of the sites investigated in a case study were moderately-high or high risk categories. It is concluded that BBN is more efficient. Both methods can easily be used to analyze environmental problems involving complex interactions among various criteria. [Display omitted] • Comparison of the application of spatial BBN and fuzzy-AHP in forest ecology. • Spatially explicit evaluation of the predisposition of bark beetle infestation. • Participatory process to quantify expert and stakeholder perceptions. • BBN approach more efficient than fuzzy-AHP. [ABSTRACT FROM AUTHOR]

• Applying the MCDM process for MUT location selection based on spatial data. • Defining the criteria that influence the MUT location selection. • Defining the required GIS datasets for quantifying the score of each street segment. • Comparing the ranking results AHP and ANP combined with TOPSIS. • Developing a prototype system to integrate the MCDM methods in a GIS platform. Multi-purpose utility tunnels (MUTs) integrate all underground utilities in one accessible tunnel. MUTs reduce the need for excavations and their associated costs, as well as the resulting traffic congestion. Several MUTs have been implemented in different parts of the world. Their locations have either been politically influenced or selected to preserve heritage sites or to meet the conditions of a newly developed city. Nevertheless, selecting the location in an existing city under street segments is affected by several criteria that have different spatial characteristics. Combining these characteristics and managing the trade-offs that exist between them determine the ranking of alternative MUT locations. The use of subjective and objective weights in the decision-making process will offer different perspectives from the decision-maker's perspective and the data itself, respectively. This paper aims to analyze spatial data as an input in the multi-criteria decision-making (MCDM) process of the MUT location selection. The objectives are: (1) defining the criteria that influence the MUT location selection, (2) defining the required GIS datasets for quantifying the criteria as scores for each candidate street segment, (3) analyzing the impacts of the dependencies between the criteria by comparing the ranking results of two MCDM methods (i.e., Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP)) combined with the Technique for Order Preference by the Similarity to Ideal Solution (TOPSIS), (4) analyzing the difference between using subjective weights or objective weights, and (5) developing a prototype system to integrate the MCDM methods in a GIS platform. A vector-based spatial analysis is conducted to identify the suitable locations for MUT construction based on 12 criteria representing physical condition information or affecting social costs. Two subjective MCDM methods (i.e., AHP and ANP) are used to generate each criterion's weights, and the ranking of alternatives is determined using TOPSIS. Another set of weights representing the objective weights are calculated for each criterion using the Shannon Entropy method. These weights are combined with TOPSIS to obtain an objective ranking of the alternatives. Based on the results from the different combinations (AHP + TOPSIS, ANP + TOPSIS, and ENTROPY + TOPSIS), the top alternative is always the same. [ABSTRACT FROM AUTHOR]