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Risk management plays a vital role in ensuring the safety and efficiency of tunnel construction by considering various factors, including uncertainties associated with concurrent adverse sources. One key aspect of risk management is prioritizing hazardous zones to devise an optimal countermeasure plan within time and cost constraints. This study developed an advanced tunnel risk management model, combining the analytic hierarchy process (AHP) and fuzzy set theory (FST). The model derived the impact using AHP and the probability using FST. By selectively combining causal factors that met the selection criterion, the risk of each hazardous zone was determined, enabling the prioritization of identified hazardous zones. The model application results indicated that causal combinations associated with significant tunnel convergence posed a relatively high risk. Moreover, the hazardous zones where unstable ground formations were excavated by a gripper tunnel boring machine (TBM) were revealed as the most vulnerable locations. Consequently, adopting a shield TBM or implementing ground reinforcement is recommended. Overall, the developed model effectively prioritizes identified hazardous zones and provides an optimal countermeasure plan, contributing to the overall safety and efficiency of the operations.

Purpose: To reduce the subjective prejudice and uncertainty in evaluating product quality. Design/methodology/approach: AHP method is used to analyze the structure of product quality evaluation problem and determine weights for evaluation criteria. After structure judge matrix, sequencing calculation and concordance examination, evaluation methods such as fuzzy synthesis evaluation are used to calculate the integrated quality evaluation result of each product. Findings: A new model is proposed by comprehensively using AHP method, weighted comprehensive evaluation and fuzzy comprehensive evaluation. A practical example of a product has been used to illustrate the theoretical qualitative proposed evaluation model. Practical implications: The result of this research offers a new method for the enterprises production quality management. Originality/value: Using AHP fuzzy comprehensive evaluation method in building product quality evaluation system.

Lao PDR faces seasonal power supply problems due to its heavy reliance on hydropower. Thus, the aim of this paper was to prioritize renewable energy (RE) resources for sustainable electricity generation in Lao PDR using the analytic hierarchy process (AHP) method, and to further estimate the energy available for the prioritized RE to enhance the seasonal power supply. Four RE alternatives were assessed considering technological, economic, environmental, and social criteria with twelve overall sub-criteria. The results indicated that hydropower was the most highly prioritized alternative, followed by solar. The resulting weights of the RE prioritization were in agreement with the Lao energy policy and plan. In order to address the seasonal power supply problem, setting-up floating photovoltaic (FPV) units in the existing hydropower reservoirs was proposed. The FPV potential was estimated, and the results revealed that the predicted power demand by 2030, as calculated in the latest Lao national power development strategy, could be fully covered by integrating the FPV output from 10% coverage of the water surface in four existing hydropower reservoirs with the existing power supply in 2020. The proposed FPV technology would provide a solution to enhance the seasonal power supply and reduce the power import.

This study aims at providing expertise for preparing public-based flood mapping and estimating flood risks in growing urban areas. To model and predict the magnitude of flood risk areas, an integrated Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) analysis techniques are used for the case of Eldoret Municipality in Kenya. The flood risk vulnerability mapping follows a multi-parametric approach and integrates some of the flooding causative factors such as rainfall distribution, elevation and slope, drainage network and density, land-use/land-cover and soil type. From the vulnerability mapping, urban flood risk index (UFRI) for the case study area, which is determined by the degree of vulnerability and exposure is also derived. The results are validated using flood depth measurements, with a minimum average difference of 0.01 m and a maximum average difference of 0.37 m in depth of observed flooding in the different flood prone areas. Similarly with respect to area extents, a maximum error of not more than 8% was observed in the highly vulnerable flood zones. In addition, the Consistency Ratio which shows an acceptable level of 0.09 was calculated and further validated the strength of the proposed approach.

The development of landslide susceptibility maps is of great importance due to rapid urbanization. The purpose of this study is to present a method to integrate the subjective weight with objective weight for regional landslide susceptibility mapping on the geographical information system (GIS) platform. The analytical hierarchy process (AHP), which is subjective, was employed to weight predictive factors’ contribution to landslide occurrence. The frequency ratio (FR) method, which is objective, was used to derive subclasses’ frequency ratio with respect to landslides that indicate the relative importance of a subclass within each predictive factor. A case study was carried out at Tsushima Island, Japan, using a historical inventory of 534 landslides and seven predictive factors: elevation, slope, aspect, terrain roughness index (TRI), lithology, land cover and mean annual precipitation (MAP). The landslide susceptibility index (LSI) was calculated using the weighted linear combination of factors’ weights and subclasses’ weights. The study area was classified into five susceptibility zones according to the LSI. In addition, the produced susceptibility map was compared with maps generated using the conventional FR and AHP method and validated using the relative landslide index (RLI). The validation result showed that the proposed method performed better than the conventional application of the FR method and AHP method. The obtained landslide susceptibility maps could serve as a scientific basis for urban planning and landslide hazard management.

China has achieved the goal of building a moderately prosperous society in a well-rounded way by 2020. At this stage, effectively dealing with poverty and not returning to it has become the bottom-line task of rural revitalization. The purpose of this study is to construct a poverty-return early warning and evaluation system for X and Y counties in Guangxi. Based on the field survey data of 150 households from the questionnaire survey in X County and Y County of Guangxi Province, an early warning evaluation system for returning to poverty in the two counties of Guangxi Province is constructed. The AHP analytic hierarchy process is used to evaluate the early warning of returning to poverty for farmers. The BP neural network algorithm is used to verify the rationality of the method; the overall poverty relief situation in the two counties is stable and the living conditions are good. The early warning results are as follows: One household in X County has a severe early warning, six households have a slight early warning, and sixty-four households have no early warning; in Y County, six households had severe early warning, six households had mild early warning, and sixty-seven households had no early warning. For farmers, serious early warnings are mainly caused by the lack of labor force and low annual per capita net income, as well as the lack of the main means of livelihood and capacity. The characteristics of mild early warnings for farmers are mainly that the proportion of non-labor income is relatively high, and the farmers lack the ability and way of long-term development. Different suggestions are put forward for farmers with different early-warning levels, focusing on improving their viability and development ability.

Currently, the Chinese government is promoting the transformation of clean energy in rural areas to reduce the consumption of coal to cope with the smog. It is mainly based on “coal to gas”. The development of biomass resources in agricultural areas is an alternative means of energy supply. In order to improve rural energy structure, we propose to upgrade “coal to gas” to “coal to biomass” derived from centralized biogas production (CBP) and straw-briquetting fuel (SBF). This study deals with the question of financing such projects. The public–private partnership (PPP) model is seen as a response that can mobilize social capital to finance investments in these new modes of production and energy supply in rural areas. Based on an analysis of the strengths, weaknesses, opportunities and threats (SWOT) of the two projects considered above, an analytic hierarchy process (AHP) was carried out with the assistance of experts in order to clarify the strategic choices which are more suitable for investors. First, we built a PPP strategic-decision model. The decision model was divided into four strategies (pioneering strategy, struggling strategy, conservative strategy and striving strategy) and two development intensities (conservative and proactive). We used this method to construct a SWOT–AHP model of the PPP strategy for CBP and SBF based on the investigation from the experts. The strategic-decision model identified that a pioneering strategy based on opportunity type is promised for SBF, while a more aggressive type strategy in struggling strategy is essential for the CBP. In order to encourage investors to adopt a positive and optimistic attitude towards the two projects, the public authorities have a role of guidance to ensure the mobilization of the social capital necessary for the construction of the projects.

The spread of invasive species (IS) has the potential to upset ecosystem balances. In extreme cases, this can hinder economical utilization of both aquatic (fisheries) and terrestrial (agricultural) systems. As a result, many countries regard risk assessment of IS as an important process for solving the problem of biological invasion. Yet, some IS are purposefully introduced for what is seen as their potential economic benefits. Thus, conducting IS risk assessments and then formulating policies based on scientific information will allow protocols to be developed that can reduce problems associated with IS incursions, whether occurring purposefully or not. However, the risk assessment methods currently adopted by most countries use qualitative or semiquantitative methodologies. Currently, there is a mismatch between qualitative and quantitative assessments. Moreover, most assessment systems are for terrestrial animals. What is needed is an assessment system for aquatic animals; however, those currently available are relatively rudimentary. To fill this gap, we used the analytic hierarchy process (AHP) to build a risk assessment model system for aquatic IS. Our AHP has four primary indexes, twelve secondary indexes, and sixty tertiary indexes. We used this AHP to conduct quantitative risk assessments on five aquatic animals that are typically introduced in China, which have distinct biological characteristics, specific introduction purposes, and can represent different types of aquatic animals. The assessment results show that the risk grade for Pterygoplichthys pardalis is high; the risk grade for Macrobrachium rosenbergii, Crassostrea gigas, and Trachemys scripta elegans is medium; and the grade risk for Ambystoma mexicanum is low. Risk assessment of the introduction of aquatic animals using our AHP is effective, and it provides support for the introduction and healthy breeding of aquatic animals. Thus, the AHP model can provide a basis for decision-making risk management concerning the introduction of species.

Dairy farming is a subsidiary profession of agriculture in India where dairy cooperatives are an important part of rural development. The current study explores the critical factors in the dairy supply chain, and provides an initial decision framework for its implications. The necessary data were collected from dairy producer members including dairy farmers, executives, and key informants of processing units, to summarize the strengths, weaknesses, opportunities, threats (SWOT) of the milk processing system in India. This includes identifying the objectives of the dairy industry, along with the internal and external critical factors (CFs). SWOT exploration does not offer any investigative basis for evaluating the priorities of CFs, therefore the analytic hierarchy process is applied to define the priorities of identified CFs. The CFs have also been ordered according to relative importance. The findings of this study depict that the SWOT based methodology offers vital sensitivity in assessing the supply chain strategies for the dairy industry.

This study proposes a multi-criteria analysis for the prioritization of alternatives for POCT blood gas analysis equipment procurement in a high-complexity healthcare institution through the Analytic Hierarchy Process (AHP). This work is presented as a tool for hospitals and is based on the Health Technology Assessment (HTA) model that supports the decision-making process in the acquisition of medical equipment. For this, criteria, sub-criteria and assessment instruments were identified based on the Core and mini-HTA models, review of scientific articles and healthcare institution requirements for high-complexity healthcare. The proposed approach was applied to the procurement process of POCT equipment in a healthcare institution in the city of Santiago de Cali-Colombia. As a result, the current procurement process was simplified by identifying five criteria and eleven sub-criteria that allowed the prioritization of POCT blood gas analysis equipment alternatives. Furthermore, three criteria with greater relevance were identified in the technological selection process.