scholarly journals Using an improved interval technique for order preference by similarity to ideal solution to assess river ecosystem health

2019 ◽  
Vol 21 (4) ◽  
pp. 624-637
Author(s):  
Wei Xu ◽  
Zengchuan Dong ◽  
Li Ren ◽  
Jie Ren ◽  
Xike Guan ◽  
...  
Keyword(s):  
Ecosystem Health ◽  
Assessment System ◽  
Ideal Solution ◽  
River Ecosystem ◽  
Interval Numbers ◽  
Aquatic Life ◽  
Morphological Form ◽  
Standard Interval ◽  
Order Preference ◽  
The Mean

Abstract A river ecosystem health (REH) assessment system, based on indicators for morphological form, hydrology features, aquatic life, and habitat provision was established to characterize REH. The standard interval Technique for Order Preference by Similarity to Ideal Solution method (TOPSIS) does not fully consider dynamic changes in REH, so interval numbers and the mean were introduced into an improved version of TOPSIS to achieve a more objective analysis. The improved interval TOPSIS method was tested in the Zhangweinan River and a river ecosystem health integrated index (REHI) was calculated. The REHI decreased from 0.376 to 0.346 over the past 25 years and the REH ranged from general to poor for 1991 to 1995 and from poor to very poor for 1996 to 2000, 2001 to 2005, 2006 to 2010, and 2011 to 2015. The ecosystem health is poor because of dams and reservoirs in the upper reaches that prevent water flowing to the lower reaches, over-abstraction of water, and severe pollution. This method gives objective and accurate assessments of REH and can be used to support decision-making and evaluation in a range of fields.

scholarly journals A Novel Extension of the Technique for Order Preference by Similarity to Ideal Solution Method with Objective Criteria Weights for Group Decision Making with Interval Numbers

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1460
Author(s):  
Dariusz Kacprzak
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Ease Of Use ◽  
Decision Makers ◽  
Ideal Solution ◽  
Interval Numbers ◽  
Group Matrix ◽  
Order Preference ◽  
Criteria Weights

This paper presents an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with objective criteria weights for Group Decision Making (GDM) with Interval Numbers (INs). The proposed method is an alternative to popular and often used methods that aggregate the decision matrices provided by the decision makers (DMs) into a single group matrix, which is the basis for determining objective criteria weights and ranking the alternatives. It does not use an aggregation operator, but a transformation of the decision matrices into criteria matrices, in the case of determining objective criteria weights, and into alternative matrices, in the case of the ranking of alternatives. This ensures that all the decision makers’ evaluations are taken into account instead of their certain average. The numerical example shows the ease of use of the proposed method, which can be implemented into common data analysis software such as Excel.

Interval TOPSIS with a novel interval number comprehensive weight for threat evaluation on uncertain information

2021 ◽  
pp. 1-17
Author(s):  
Chen Xiang ◽  
Wang Xing ◽  
Zhang Hubiao ◽  
Xu Yuheng ◽  
Chen You ◽  
...  
Keyword(s):  
Decision Making ◽  
Situation Awareness ◽  
Interval Number ◽  
Uncertain Information ◽  
Interval Numbers ◽  
Subjective Weight ◽  
Order Preference ◽  
The Mean ◽  
Deviation Method ◽  
Threat Evaluation

Threat evaluation (TE) is essential in battlefield situation awareness and military decision-making. The current processing methods for uncertain information are not effective enough for their excessive subjectivity and difficulty to obtain detailed information about enemy weapons. In order to optimize TE on uncertain information, an approach based on interval Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and the interval SD-G1 (SD standard deviation) method is proposed in this article. By interval SD-G1 method, interval number comprehensive weights can be calculated by combining subjective and objective weights. Specifically, the subjective weight is calculated by interval G1 method, which is an extension of G1 method into interval numbers. And the objective weight is calculated by interval SD method, which is an extension of SD method with the mean and SD of the interval array defined in this paper. Sample evaluation results show that with the interval SD-G1 method, weights of target threat attributes can be better calculated, and the approach combining interval TOPSIS and interval SD-G1 can lead to more reasonable results. Additionally, the mean and SD of interval arrays can provide a reference for other fields such as interval analysis and decision-making.

Assessment of Ecosystem Health of Panlong River, an Urban River in Kunming City

2013 ◽  
Vol 742 ◽  
pp. 427-431
Author(s):  
Jun Mei Li ◽  
Zhao Lu Wu ◽  
Yu Fei ◽  
Shu Zhuang He ◽  
Jie He
Keyword(s):  
Water Quality ◽  
Ecosystem Health ◽  
Riparian Zone ◽  
River Channel ◽  
Urban River ◽  
Assessment Model ◽  
River Ecosystem ◽  
Aquatic Life ◽  
Comprehensive Index ◽  
Study Results

Healthy urban river ecosystem is the important symbol of the sustaining development of a city. This thesis discussed the issues of the ecosystem health situation of Panlong River, an urban river in Kunming city. This can provide the reference and scientific strategy for the government to renovate the urban river comprehensively. Using the comprehensive index evaluation method, we selected some indicators to characterize the main features and functions of urban river ecosystem to establish a comprehensive index system for evaluating urban river ecosystem health. These indicators included six aspects: water quality indicators, aquatic life indicators, hydrology indicators, river channel indicators, riparian zone indicators and social indicators. Total of them are 20 indicators. And the evaluation criteria was ascertained. Analytic hierarchy process (AHP) method was used to determine the weight of the indicators and the comprehensive assessment model was also built. Pilot study results indicate that the ecosystem of Panlong River in Kunming city is in the health status in 2011. The results showed that the comprehensive renovation of the Panlong River was very effective. Based on the ecosystem health assessment results of Panlong Rive and evaluation score of each indicator, we made certain the limiting factors that affect the urban river ecosystem health, which are vegetation of riparian zone, the water quality, aquatic habitat, the curve situation of the river channel, the form of bank protection, etc. And some suggestions were also provided for Panlong River ecological restoration.

scholarly journals IMPLEMENTATION TECHNIQUE METHOD FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) IN ASSESMENT OF DOG CHARACTERISTICS SYSTEM

2019 ◽  
Vol 2 (2) ◽  
pp. 171-180
Author(s):  
Christine ◽  
Halim Agung
Keyword(s):  
Assessment System ◽  
Ideal Solution ◽  
Topsis Method ◽  
Kennel Club ◽  
Order Preference ◽  
Filter Process ◽  
Negative Ideal Solution ◽  
Topsis Technique ◽  
Different Characteristics ◽  
Implementation Technique

Dogs are the most populated animals in 2016 according to a survey of pet populations by the UK's association of animal food makers (PFMA). With so many types of dogs and different characteristics, not all humans can choose the type of dog that suits their situation and condition. These non-conformities cause dogs to be dumped on the streets or abandoned without proper care. Therefore the dog characteristics assessment system is made which aims to facilitate the user in choosing the type of dog that is suitable for the user's situation and condition. This system is made using the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution). This system is based on the data of dogs registered with the AKC (American Kennel Club). This system uses eight criteria, three criteria for the filter process and five criteria for the weighting process. Of the five weighting criteria, there are three cost attributes and two benefit attributes. In the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) uses the principle that the chosen alternative must have the closest distance from the positive ideal solution and the longest (farthest) distance from the negative ideal solution. The results obtained from this assessment system are by theory-based testing 50 times with a 78% suitability match percentage. The conclusion obtained from this research is the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is quite efficient to be applied in a dog characteristic assessment system

scholarly journals IMPLEMENTATION TECHNIQUE METHOD FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) IN ASSESMENT OF DOG CHARACTERISTICS SYSTEM

2019 ◽  
Vol 2 (2) ◽  
pp. 171-180
Author(s):  
Christine ◽  
Halim Agung
Keyword(s):  
Assessment System ◽  
Ideal Solution ◽  
Topsis Method ◽  
Kennel Club ◽  
Order Preference ◽  
Filter Process ◽  
Negative Ideal Solution ◽  
Topsis Technique ◽  
Different Characteristics ◽  
Implementation Technique

Dogs are the most populated animals in 2016 according to a survey of pet populations by the UK's association of animal food makers (PFMA). With so many types of dogs and different characteristics, not all humans can choose the type of dog that suits their situation and condition. These non-conformities cause dogs to be dumped on the streets or abandoned without proper care. Therefore the dog characteristics assessment system is made which aims to facilitate the user in choosing the type of dog that is suitable for the user's situation and condition. This system is made using the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution). This system is based on the data of dogs registered with the AKC (American Kennel Club). This system uses eight criteria, three criteria for the filter process and five criteria for the weighting process. Of the five weighting criteria, there are three cost attributes and two benefit attributes. In the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) uses the principle that the chosen alternative must have the closest distance from the positive ideal solution and the longest (farthest) distance from the negative ideal solution. The results obtained from this assessment system are by theory-based testing 50 times with a 78% suitability match percentage. The conclusion obtained from this research is the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is quite efficient to be applied in a dog characteristic assessment system

TERAPAN KOMBINASI METODE TOPSIS DAN ANALYTICAL HIERARCHY PROCESS PADA PEREKOMENDASIAN PENERIMA BEASISWA PENINGKATAN PRESTASI AKADEMIK (Studi Kasus pada STMIK PPKIA Tarakanita Rahmawati)

2017 ◽  
Vol 8 (2) ◽  
pp. 663 ◽  
Author(s):  
Muhammad Fadlan ◽  
Muhammad Muhammad ◽  
Hadriansa
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
Ideal Solution ◽  
Microsoft Excel ◽  
Order Preference ◽  
Hierarchy Process

Beasiswa Peningkatan Prestasi Akademik (PPA) sebagai salah satu bentuk dukungan pemerintah Republik Indonesia terhadap dunia pendidikan. Beasiswa yang disalurkan oleh pemerintah melalui Perguruan Tinggi yang ada di Indonesia ini, penyeleksian dan penetapan penerimanya sepenuhnya diserahkan kepada pihak Perguruan Tinggi yang bersangkutan. Tahap inilah yang sangat rentan terjadinya kecurangan. Pada objek penelitian  yang diteliti hingga saat ini proses penyeleksian masih dilakukan dengan menggunakan Microsoft Excel, hal ini tentu saja kurang efektif dan efisien, serta rentan akan terjadinya kesalahan bahkan kecurangan. Untuk itu, diperlukan suatu metodologi dan aplikasi yang tepat dalam melakukan penyeleksian penerima beasiswa tersebut. Decision Support System digunakan sebagai solusi untuk melakukan perekomendasian penerima beasiswa, khususnya dengan menggunakan Metode Technique  for  Order  Preference  by  Similarity  to  Ideal  Solution  (TOPSIS)  dan  Analytical  Hierarcy Process (AHP). Penggunaan kombinasi dua metode tersebut dilakukan agar memiliki tingkat akurasi yang baik jika dibandingkan  dengan menggunakan satu metode. Hasilnya,  aplikasi  decision support system dengan penerapan kombinasi metode Topsis dan AHP berhasil di rancang dan di ujicoba, serta sukses dalam perekomendasian penerima beasiswa PPA dengan menghasilkan data alternatif mahasiswa yang terurut mulai dari nilai preferensi yang paling tinggi 0.764 hingga terendah 0.189. Hasil ini dapat menjadi rekomendasi bagi pengambil keputusan dalam mengambil keputusan yang efektik, efisien dan dapat dipertanggung jawabkan.

scholarly journals Malmquist Productivity Index by Extended VIKOR Method Using Interval Numbers

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Mohammad Fallah ◽  
Amir Mohajeri ◽  
Esmaeil Najafi
Keyword(s):  
Multicriteria Decision Making ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Ideal Solution ◽  
Vikor Method ◽  
Decision Matrix ◽  
Interval Numbers ◽  
Productivity Rate ◽  
The Given ◽  
The Ideal

The VIKOR method was developed for multicriteria optimization of complex systems. It determines the compromise ranking list and the compromise solution obtained with the given weights. This method focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria. Here, the VIKOR method is used for two timestandt+1. In order to calculate the progress or regression via Malmquist productivity index, the positive and negative ideals at timestandt+1are calculated first. Then we introduce the multi-criteria ranking index based on the particular measure of “closeness” to the ideal solution and calculate the separation of each alternative from the ideal solution at timestandt+1. Then we use the Malmquist productivity index to calculate the progress or regression of all alternatives. In this paper, productivity of alternatives available in decision matrix with interval numbers and their improvement or deterioration is researched. To achieve this practical goal, use of extended VIKOR is made to calculate Malmquist productivity index for multicriteria decision-making (MCDM) problem with interval numbers, and by applying Malmquist productivity index, productivity rate of growth for alternatives is calculated. Finally, a numerical example illustrates and clarifies the main results developed in this paper.

Radiator threat evaluation with missing data based on improved technique for order preference by similarity to ideal solution

2021 ◽  
pp. 1-10
Author(s):  
Yu-Heng Xu ◽  
Si-Yi Cheng ◽  
Hu-Biao Zhang
Keyword(s):  
Missing Data ◽  
Prior Knowledge ◽  
Attribute Reduction ◽  
Estimation Algorithm ◽  
Weighted Averaging ◽  
Ideal Solution ◽  
Attribute Weights ◽  
Order Preference ◽  
Improved Technique ◽  
Threat Evaluation

To solve the problem of the missing data of radiator during the aerial war, and to address the problem that traditional algorithms rely on prior knowledge and specialized systems too much, an algorithm for radiator threat evaluation with missing data based on improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been proposed. The null estimation algorithm based on Induced Ordered Weighted Averaging (IOWA) is adopted to calculate the aggregate value for predicting missing data. The attribute reduction is realized by using the Rough Sets (RS) theory, and the attribute weights are reasonably allocated with the theory of Shapley. Threat degrees can be achieved through quantization and ranking of radiators by constructing a TOPSIS decision space. Experiment results show that this algorithm can solve the incompleteness of radiator threat evaluation, and the ranking result is in line with the actual situation. Moreover, the proposed algorithm is highly automated and does not rely on prior knowledge and expert systems.

scholarly journals Socioeconomic Risks and Their Impacts on Ecological River Health in South Korea: An Application of the Analytic Hierarchy Process

2021 ◽  
Vol 13 (11) ◽  
pp. 6287
Author(s):  
Suyeon Kim ◽  
Sang-Woo Lee ◽  
Se-Rin Park ◽  
Yeeun Shin ◽  
Kyungjin An
Keyword(s):  
South Korea ◽  
Socioeconomic Factors ◽  
Ecosystem Health ◽  
Relative Importance ◽  
River Ecosystem ◽  
River Health ◽  
Analytic Hierarchy ◽  
Factors Affecting ◽  
Factors Influencing ◽  
Hierarchy Process

It is imperative to develop a methodology to identify river impairment sources, particularly the relative impact of socioeconomic sources, to enhance the efficiency of various river restoration schemes and policies and to have an internal diagnosis system in place. This study, therefore, aims to identify and analyze the relative importance of the socioeconomic factors affecting river ecosystem impairment in South Korea. To achieve this goal, we applied the Analytical Hierarchy Process (AHP) to evaluate expert judgement of the relative importance of different socioeconomic factors influencing river ecosystem impairment. Based on a list of socioeconomic factors influencing stream health, an AHP questionnaire was prepared and administered to experts in aquatic ecology. Our analysis reveals that secondary industries form the most significant source of stream ecosystem impairment. Moreover, the most critical socioeconomic factors affecting stream impairment are direct inflow pollution, policy implementation, and industrial wastewater. The results also suggest that the AHP is a rapid and robust approach to assessing the relative importance of different socioeconomic factors that affect river ecosystem health. The results can be used to assist decision makers in focusing on actions to improve river ecosystem health.

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