Geo-Information Driven Multi-Criteria Decision Analysis for Precision Agriculture Technologies Using Neutrosophic Entropy-DEMATEL and Hybrid TOPSIS
Abstract
1. Introduction
- To explore and evaluate the core types of ten precision agriculture technologies based on insights from academic research and real-world applications.
- To define ten key assessment criteria for the practical evaluation of these technologies.
- To conduct a comparative study that identifies the advantages, drawbacks, and real-world applicability of various technologies across different agricultural settings.
- To focus on recognizing technologies that are particularly suitable for the needs and constraints of small and medium-scale farming sectors.
- To develop practical recommendations that can assist farmers, researchers, and policymakers in making informed decisions about adopting precision agriculture technologies.
2. Materials and Methods
2.1. Description of Existing Methods
2.2. Collection of Data and Data Preprocessing
Questionnaire Structure and Expert Evaluation Procedure
2.3. Preliminaries
- (i)
- (ii)
- (iii)
- (iv)
- (v)
- (vi)
2.4. Similarity Measure
3. Proposed Method for Weight Determination and Ranking Utilizing Neutrosophic Entropy-DEMATEL and Neutrosophic TOPSIS with a Hybrid Similarity Measure
3.1. Proposed Similarity Measure Formula [75]: Hybrid Weighted Cosine-Jaccard Neutrosophic Similarity Measure
3.2. Proposed Methodology
3.2.1. Application of Entropy Method
3.2.2. Neutrosophic Entropy Method [73]
- Step 1. A brief overview of the investigation factors was constructed.
- Step 2. Participants in the survey were experts or decision makers.
| Linguistic Term | Abbreviation | SVNNs | ||
|---|---|---|---|---|
| T | I | F | ||
| Extremely Bad | EB | 0.00 | 1.00 | 1.00 |
| Very Very Bad | VVB | 0.10 | 0.90 | 0.90 |
| Very Bad | VB | 0.20 | 0.85 | 0.80 |
| Bad | B | 0.30 | 0.75 | 0.70 |
| Medium Bad | MB | 0.40 | 0.65 | 0.60 |
| Medium | M | 0.50 | 0.50 | 0.50 |
| Medium Good | MG | 0.60 | 0.35 | 0.40 |
| Good | G | 0.70 | 0.25 | 0.30 |
| Very Good | VG | 0.80 | 0.15 | 0.20 |
| Very Very Good | VVG | 0.90 | 0.10 | 0.10 |
| Extremely Good | EG | 1.00 | 0.00 | 0.00 |
- Step 3. Aggregated and normalized decision matrix.
- Step 4. Determine each criterion’s entropy value in the decision matrix.
- Step 5. Compute the entropy’s weight for each criterion.
3.2.3. Application of DEMATEL Method
3.2.4. Neutrosophic DEMATEL Method [62]
- Step 1. Determine the neutrosophic aggregated direct-influence matrix (DIM), denoted as .
- Step 2. Normalize the neutrosophic aggregated DIM to obtain a matrix , as shown in Equations (4) and (5).
- Step 3. Evaluate the total DIM by using the following formula:where , and
3.2.5. Hybrid Weighting Approach [77]
3.2.6. Application of TOPSIS Method
3.2.7. Neutrosophic TOPSIS Method [62]
- Step 1. Aggregated neutrosophic decision matrix (NDM) [45].
- Step 2. Normalized aggregated NDM.
- Step 3. Weighted normalized aggregated NDM.
- Step 4. Obtain neutrosophic PIS and NIS.
- Step 5. Compute the hybrid similarity measure of each alternative from the neutrosophic PIS and NIS.
- Step 6. Calculation of the relative closeness coefficient ( with respect to the neutrosophic ideal solution.
- Step 7. Compute the rank of each alternative.
4. Real Life Application and Results
4.1. Empirical Results
4.1.1. Calculations of Neutrosophic Entropy Values
4.1.2. Calculations of Neutrosophic DEMATEL Values
| Criteria | ||||
|---|---|---|---|---|
| 7.90 | 8.24 | 16.13 | −0.34 | |
| 7.59 | 8.29 | 15.89 | −0.70 | |
| 8.59 | 8.31 | 16.90 | 0.29 | |
| 7.80 | 8.23 | 16.02 | −0.43 | |
| 8.47 | 8.12 | 16.59 | 0.35 | |
| 8.19 | 8.45 | 16.64 | −0.26 | |
| 7.68 | 7.56 | 15.24 | 0.12 | |
| 8.48 | 8.40 | 16.88 | 0.08 | |
| 8.74 | 8.00 | 16.74 | 0.74 | |
| 8.04 | 7.89 | 15.92 | 0.15 |
4.1.3. Calculations of Neutrosophic TOPSIS
| Alternatives | Cosine Similarity Measure | Jaccard Similarity Measure | ||
|---|---|---|---|---|
| RCC | Rank | RCC | Rank | |
| 0.51 | 2 | 0.51 | 2 | |
| 0.48 | 5 | 0.47 | 5 | |
| 0.48 | 6 | 0.47 | 4 | |
| 0.37 | 10 | 0.30 | 10 | |
| 0.40 | 9 | 0.35 | 9 | |
| 0.50 | 3 | 0.49 | 3 | |
| 0.43 | 8 | 0.40 | 8 | |
| 0.49 | 4 | 0.47 | 6 | |
| 0.46 | 7 | 0.43 | 7 | |
| 0.54 | 1 | 0.55 | 1 | |
4.1.4. Sensitivity Analysis of Weight Selection
4.1.5. Comparative Analysis of Weighting Schemes
4.2. Robustness and Sensitivity Analysis of Expert Evaluations
5. Discussion of Results
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
| 0.73 | 0.71 | 0.73 | 0.75 | 0.75 | 0.67 | 0.60 | 0.60 | 0.65 | 0.77 | |
| 0.77 | 0.83 | 0.79 | 0.70 | 0.71 | 0.67 | 0.77 | 0.65 | 0.73 | 0.73 | |
| 0.76 | 0.78 | 0.77 | 0.80 | 0.83 | 0.74 | 0.71 | 0.67 | 0.75 | 0.73 | |
| 0.70 | 0.69 | 0.67 | 0.63 | 0.65 | 0.71 | 0.57 | 0.61 | 0.59 | 0.67 | |
| 0.60 | 0.65 | 0.61 | 0.56 | 0.63 | 0.61 | 0.61 | 0.63 | 0.61 | 0.63 | |
| 0.69 | 0.61 | 0.69 | 0.71 | 0.75 | 0.70 | 0.61 | 0.57 | 0.63 | 0.65 | |
| 0.77 | 0.65 | 0.69 | 0.67 | 0.68 | 0.63 | 0.63 | 0.70 | 0.74 | 0.67 | |
| 0.74 | 0.71 | 0.63 | 0.77 | 0.74 | 0.70 | 0.61 | 0.67 | 0.67 | 0.70 | |
| 0.67 | 0.67 | 0.59 | 0.67 | 0.65 | 0.68 | 0.61 | 0.65 | 0.61 | 0.65 | |
| 0.77 | 0.74 | 0.74 | 0.77 | 0.77 | 0.72 | 0.63 | 0.65 | 0.67 | 0.69 |
| 0.10 | 0.10 | 0.11 | 0.11 | 0.11 | 0.10 | 0.10 | 0.09 | 0.10 | 0.11 | |
| 0.11 | 0.12 | 0.11 | 0.10 | 0.10 | 0.10 | 0.12 | 0.10 | 0.11 | 0.11 | |
| 0.11 | 0.11 | 0.11 | 0.11 | 0.12 | 0.11 | 0.11 | 0.11 | 0.11 | 0.11 | |
| 0.10 | 0.10 | 0.10 | 0.09 | 0.09 | 0.11 | 0.09 | 0.10 | 0.09 | 0.10 | |
| 0.08 | 0.09 | 0.09 | 0.08 | 0.09 | 0.09 | 0.10 | 0.10 | 0.09 | 0.09 | |
| 0.10 | 0.09 | 0.10 | 0.10 | 0.11 | 0.10 | 0.10 | 0.09 | 0.10 | 0.10 | |
| 0.11 | 0.09 | 0.10 | 0.10 | 0.09 | 0.09 | 0.10 | 0.11 | 0.11 | 0.10 | |
| 0.10 | 0.10 | 0.09 | 0.11 | 0.10 | 0.10 | 0.10 | 0.11 | 0.10 | 0.10 | |
| 0.09 | 0.10 | 0.09 | 0.10 | 0.09 | 0.10 | 0.10 | 0.10 | 0.09 | 0.10 | |
| 0.11 | 0.11 | 0.11 | 0.11 | 0.11 | 0.11 | 0.10 | 0.10 | 0.10 | 0.10 |
| −0.23 | −0.23 | −0.24 | −0.24 | −0.24 | −0.23 | −0.22 | −0.22 | −0.23 | −0.25 | |
| −0.24 | −0.25 | −0.25 | −0.23 | −0.23 | −0.23 | −0.26 | −0.23 | −0.24 | −0.24 | |
| −0.24 | −0.24 | −0.25 | −0.25 | −0.25 | −0.24 | −0.25 | −0.24 | −0.25 | −0.24 | |
| −0.23 | −0.23 | −0.23 | −0.22 | −0.22 | −0.24 | −0.22 | −0.22 | −0.22 | −0.23 | |
| −0.21 | −0.22 | −0.21 | −0.20 | −0.21 | −0.22 | −0.22 | −0.23 | −0.22 | −0.22 | |
| −0.22 | −0.21 | −0.23 | −0.23 | −0.24 | −0.23 | −0.22 | −0.22 | −0.22 | −0.22 | |
| −0.24 | −0.22 | −0.23 | −0.23 | −0.22 | −0.22 | −0.23 | −0.24 | −0.24 | −0.23 | |
| −0.23 | −0.23 | −0.22 | −0.24 | −0.23 | −0.23 | −0.23 | −0.24 | −0.23 | −0.23 | |
| −0.22 | −0.22 | −0.21 | −0.22 | −0.22 | −0.23 | −0.23 | −0.23 | −0.22 | −0.22 | |
| −0.24 | −0.24 | −0.24 | −0.24 | −0.24 | −0.24 | −0.23 | −0.23 | −0.23 | −0.23 | |
| Total | −0.23 | −0.23 | −0.24 | −0.24 | −0.24 | −0.23 | −0.22 | −0.22 | −0.23 | −0.25 |
| (0.10, 0.80, 0.90) | (0.77, 0.21, 0.21) | (0.47, 0.44, 0.50) | (0.78, 0.21, 0.22) | (0.68, 0.30, 0.33) | |
| (0.72, 0.25, 0.25) | (0.10, 0.80, 0.90) | (0.86, 0.14, 0.14) | (0.83, 0.17, 0.14) | (0.47, 0.44, 0.50) | |
| (0.87, 0.13, 0.12) | (0.88, 0.12, 0.11) | (0.10, 0.80, 0.90) | (0.88, 0.12, 0.11) | (0.83, 0.17, 0.14) | |
| (0.84, 0.16, 0.15) | (0.72, 0.26, 0.23) | (0.88, 0.12, 0.11) | (0.10, 0.80, 0.90) | (0.78, 0.20, 0.20) | |
| (0.76, 0.23, 0.23) | (0.81, 0.17, 0.18) | (0.75, 0.24, 0.19) | (0.73, 0.24, 0.25) | (0.10, 0.80, 0.90) | |
| (0.50, 0.47, 0.45) | (0.50, 0.47, 0.45) | (0.73, 0.24, 0.25) | (0.65, 0.31, 0.30) | (0.74, 0.26, 0.21) | |
| (0.29, 0.65, 0.68) | (0.46, 0.47, 0.50) | (0.69, 0.29, 0.26) | (0.29, 0.65, 0.68) | (0.26, 0.67, 0.77) | |
| (0.78, 0.20, 0.20) | (0.81, 0.17, 0.18) | (0.74, 0.26, 0.21) | (0.83, 0.17, 0.14) | (0.61, 0.32, 0.36) | |
| (0.65, 0.31, 0.30) | (0.65, 0.31, 0.30) | (0.74, 0.26, 0.21) | (0.43, 0.47, 0.53) | (0.88, 0.12, 0.11) | |
| (0.61, 0.36, 0.39) | (0.50, 0.47, 0.45) | (0.28, 0.61, 0.69) | (0.57, 0.37, 0.39) | (0.61, 0.36, 0.39) | |
| (0.65, 0.32, 0.33) | (0.17, 0.75, 0.85) | (0.78, 0.20, 0.20) | (0.65, 0.31, 0.30) | (0.62, 0.36, 0.39) | |
| (0.50, 0.47, 0.45) | (0.31, 0.61, 0.70) | (0.81, 0.17, 0.70) | (0.21, 0.72, 0.82) | (0.50, 0.47, 0.45) | |
| (0.86, 0.14, 0.14) | (0.59, 0.38, 0.35) | (0.89, 0.12, 0.11) | (0.52, 0.42, 0.45) | (0.28, 0.61, 0.69) | |
| (0.50, 0.47, 0.45) | (0.21, 0.68, 0.77) | (0.85, 0.15, 0.13) | (0.17, 0.75, 0.85) | (0.47, 0.44, 0.50) | |
| (0.72, 0.28, 0.23) | (0.62, 0.36, 0.35) | (0.66, 0.29, 0.32) | (0.73, 0.26, 0.26) | (0.61, 0.36, 0.36) | |
| (0.10, 0.80, 0.90) | (0.85, 0.15, 0.13) | (0.28, 0.61, 0.69) | (0.90, 0.10, 0.10) | (0.85, 0.15, 0.13) | |
| (0.85, 0.15, 0.13) | (0.10, 0.80, 0.90) | (0.60, 0.34, 0.35) | (0.89, 0.11, 0.11)) | (0.90, 0.10, 0.10) | |
| (0.57, 0.36, 0.38) | (0.60, 0.34, 0.35) | (0.10, 0.80, 0.90) | (0.87, 0.13, 0.12) | (0.60, 0.34, 0.35) | |
| (0.87, 0.13, 0.12) | (0.90, 0.10, 0.10) | (0.90, 0.10, 0.10) | (0.10, 0.80, 0.90) | (0.75, 0.24, 0.19) | |
| (0.90, 0.10, 0.10) | (0.87, 0.13, 0.12) | (0.60, 0.34, 0.35) | (0.83, 0.17, 0.14) | (0.10, 0.80, 0.90) |
| (0.01, 0.12, 0.13) | (0.11, 0.03, 0.03) | (0.07, 0.06, 0.07) | (0.11, 0.03, 0.03) | (0.10, 0.04, 0.05) | |
| (0.10, 0.04, 0.04) | (0.02, 0.12, 0.13) | (0.12, 0.02, 0.02) | (0.12, 0.02, 0.02) | (0.07, 0.06, 0.07) | |
| (0.13, 0.02, 0.02) | (0.13, 0.02, 0.02) | (0.01, 0.12, 0.13) | (0.13, 0.02, 0.02) | (0.12, 0.02, 0.02) | |
| (0.12, 0.02, 0.02) | (0.10, 0.04, 0.03) | (0.13, 0.02, 0.02) | (0.01, 0.12, 0.13) | (0.11, 0.03, 0.03) | |
| (0.11, 0.03, 0.03) | (0.12, 0.03, 0.03) | (0.11, 0.03, 0.03) | (0.11, 0.03, 0.04) | (0.01, 0.12, 0.13) | |
| (0.07, 0.07, 0.07) | (0.07, 0.07, 0.07) | (0.11, 0.03, 0.04) | (0.09, 0.04, 0.04) | (0.11, 0.04, 0.03) | |
| (0.04, 0.09, 0.10) | (0.07, 0.07, 0.07) | (0.10, 0.04, 0.04) | (0.04, 0.09, 0.10) | (0.04, 0.10, 0.11) | |
| (0.11, 0.03, 0.03) | (0.12, 0.03, 0.03) | (0.11, 0.04, 0.03) | (0.12, 0.02, 0.02) | (0.09, 0.05, 0.05) | |
| (0.09, 0.05, 0.04) | (0.09, 0.05, 0.04) | (0.11, 0.04, 0.03) | (0.06, 0.07, 0.08) | (0.13, 0.02, 0.02) | |
| (0.09, 0.05, 0.06) | (0.07, 0.07, 0.07) | (0.04, 0.09, 0.10) | (0.08, 0.05, 0.06) | (0.09, 0.05, 0.06) | |
| (0.09, 0.05, 0.05) | (0.02, 0.11, 0.12) | (0.11, 0.03, 0.03) | (0.09, 0.04, 0.04) | (0.09, 0.05, 0.06) | |
| (0.07, 0.07, 0.07) | (0.04, 0.09, 0.10) | (0.12, 0.02, 0.10) | (0.03, 0.10, 0.12) | (0.07, 0.07, 0.07) | |
| (0.12, 0.02, 0.02) | (0.09, 0.06, 0.05) | (0.13, 0.02, 0.02) | (0.08, 0.06, 0.07) | (0.04, 0.09, 0.10) | |
| (0.07, 0.07, 0.07) | (0.03, 0.10, 0.11) | (0.12, 0.02, 0.02) | (0.02, 0.11, 0.12) | (0.07, 0.06, 0.07) | |
| (0.10, 0.04, 0.03) | (0.09, 0.05, 0.05) | (0.10, 0.04, 0.05) | (0.11, 0.04, 0.04) | (0.09, 0.05, 0.05) | |
| (0.01, 0.12, 0.13) | (0.12, 0.02, 0.02) | (0.04, 0.09, 0.10) | (0.13, 0.01, 0.01) | (0.12, 0.02, 0.02) | |
| (0.12, 0.02, 0.02) | (0.01, 0.12, 0.13) | (0.09, 0.05, 0.05) | (0.13, 0.02, 0.02) | (0.13, 0.01, 0.01) | |
| (0.08, 0.05, 0.06) | (0.09, 0.05, 0.05) | (0.01, 0.12, 0.13) | (0.13, 0.02, 0.02) | (0.09, 0.05, 0.05) | |
| (0.13, 0.02, 0.02) | (0.13, 0.01, 0.01) | (0.13, 0.01, 0.01) | (0.01, 0.12, 0.13) | (0.11, 0.03, 0.03) | |
| (0.13, 0.01, 0.01) | (0.13, 0.02, 0.02) | (0.09, 0.05, 0.05) | (0.12, 0.02, 0.02) | (0.01, 0.12, 0.13) |
| (0.64, 0.19, 0.22) | (0.73, 0.09, 0.10) | (0.70, 0.13, 0.15) | (0.73, 0.09, 0.11) | (0.70, 0.11, 0.13) | |
| (0.68, 0.11, 0.12) | (0.60, 0.19, 0.22) | (0.70, 0.08, 0.09) | (0.70, 0.09, 0.11) | (0.63, 0.14, 0.17) | |
| (0.84, 0.06, 0.07) | (0.85, 0.06, 0.06) | (0.75, 0.17, 0.19) | (0.84, 0.06, 0.07) | (0.82, 0.07, 0.07) | |
| (0.72, 0.09, 0.10) | (0.71, 0.10, 0.11) | (0.73, 0.07, 0.08) | (0.63, 0.19, 0.22) | (0.70, 0.09, 0.11) | |
| (0.81, 0.08, 0.09) | (0.82, 0.07, 0.08) | (0.82, 0.08, 0.08) | (0.80, 0.08, 0.09) | (0.70, 0.17, 0.20) | |
| (0.73, 0.13, 0.13) | (0.74, 0.12, 0.13) | (0.77, 0.08, 0.09) | (0.75, 0.10, 0.10) | (0.75, 0.09, 0.10) | |
| (0.63, 0.17, 0.19) | (0.66, 0.13, 0.15) | (0.69, 0.10, 0.11) | (0.63, 0.17, 0.19) | (0.62, 0.18, 0.21) | |
| (0.81, 0.08, 0.08) | (0.82, 0.07, 0.08) | (0.82, 0.08, 0.08) | (0.82, 0.07, 0.07) | (0.77, 0.10, 0.11) | |
| (0.83, 0.09, 0.09) | (0.84, 0.09, 0.09) | (0.85, 0.08, 0.07) | (0.80, 0.12, 0.13) | (0.84, 0.06, 0.06) | |
| (0.72, 0.11, 0.12) | (0.71, 0.13, 0.13) | (0.69, 0.15, 0.17) | (0.71, 0.11, 0.12) | (0.71, 0.11, 0.13) | |
| (0.73, 0.10, 0.11) | (0.55, 0.19, 0.23) | (0.75, 0.08, 0.10) | (0.67, 0.11, 0.12) | (0.65, 0.12, 0.14) | |
| (0.67, 0.13, 0.14) | (0.53, 0.17, 0.21) | (0.72, 0.08, 0.20) | (0.58, 0.18, 0.22) | (0.60, 0.14, 0.16) | |
| (0.86, 0.05, 0.06) | (0.69, 0.11, 0.11) | (0.87, 0.05, 0.06) | (0.75, 0.11, 0.12) | (0.70, 0.15, 0.17) | |
| (0.70, 0.13, 0.13) | (0.54, 0.18, 0.21) | (0.75, 0.07, 0.09) | (0.60, 0.18, 0.22) | (0.62, 0.13, 0.15) | |
| (0.83, 0.08, 0.08) | (0.68, 0.11, 0.12) | (0.82, 0.09, 0.10) | (0.76, 0.09, 0.09) | (0.73, 0.11, 0.11) | |
| (0.71, 0.18, 0.20) | (0.68, 0.09, 0.10) | (0.74, 0.15, 0.18) | (0.75, 0.07, 0.08) | (0.73, 0.08, 0.08) | |
| (0.73, 0.08, 0.09) | (0.53, 0.21, 0.25) | (0.70, 0.11, 0.13) | (0.68, 0.09, 0.10) | (0.67, 0.08, 0.10) | |
| (0.81, 0.10, 0.10) | (0.68, 0.11, 0.12) | (0.75, 0.17, 0.20) | (0.78, 0.06, 0.06) | (0.73, 0.10, 0.11) | |
| (0.89, 0.06, 0.06) | (0.76, 0.07, 0.07) | (0.89, 0.05, 0.06) | (0.73, 0.17, 0.20) | (0.79, 0.08, 0.08) | |
| (0.79, 0.06, 0.07) | (0.66, 0.09, 0.10) | (0.75, 0.10, 0.12) | (0.72, 0.09, 0.09) | (0.61, 0.19, 0.22) |
| 0.73 | 0.83 | 0.79 | 0.82 | 0.80 | 0.82 | 0.69 | 0.84 | 0.79 | 0.73 | |
| 0.79 | 0.72 | 0.82 | 0.81 | 0.75 | 0.78 | 0.69 | 0.79 | 0.71 | 0.79 | |
| 0.89 | 0.90 | 0.79 | 0.90 | 0.88 | 0.91 | 0.80 | 0.91 | 0.83 | 0.89 | |
| 0.82 | 0.81 | 0.83 | 0.73 | 0.81 | 0.80 | 0.69 | 0.84 | 0.72 | 0.82 | |
| 0.87 | 0.88 | 0.88 | 0.87 | 0.77 | 0.88 | 0.79 | 0.87 | 0.84 | 0.87 | |
| 0.81 | 0.82 | 0.85 | 0.83 | 0.84 | 0.77 | 0.80 | 0.80 | 0.84 | 0.81 | |
| 0.74 | 0.77 | 0.80 | 0.74 | 0.73 | 0.83 | 0.67 | 0.80 | 0.80 | 0.74 | |
| 0.87 | 0.88 | 0.87 | 0.88 | 0.84 | 0.86 | 0.79 | 0.79 | 0.86 | 0.87 | |
| 0.88 | 0.88 | 0.90 | 0.85 | 0.90 | 0.92 | 0.85 | 0.93 | 0.78 | 0.88 | |
| 0.81 | 0.80 | 0.78 | 0.81 | 0.81 | 0.87 | 0.79 | 0.83 | 0.82 | 0.81 |
| (0.77, 0.21, 0.23) | (0.72, 0.24, 0.28) | (0.75, 0.21, 0.25) | (1.00, 0.00, 0.00) | (1.00, 0.00, 0.00) | |
| (0.79, 0.18, 0.21) | (1.00, 0.00, 0.00) | (1.00, 0.00, 0.00) | (0.69, 0.25, 0.31) | (0.74, 0.21, 0.26) | |
| (0.76, 0.19, 0.24) | (0.77, 0.18, 0.23) | (0.80, 0.17, 0.20) | (0.79, 0.16, 0.21) | (1.00, 0.00, 0.00) | |
| (0.69, 0.25, 0.31) | (0.69, 0.26, 0.31) | (0.69, 0.26, 0.31) | (0.65, 0.31, 0.35) | (0.67, 0.29, 0.33) | |
| (1.00, 0.00, 0.00) | (0.68, 0.27, 0.32) | (0.64, 0.32, 0.36) | (0.61, 0.36, 0.39) | (0.67, 0.29, 0.33) | |
| (0.72, 0.25, 0.28) | (0.62, 0.35, 0.38) | (0.71, 0.24, 0.29) | (1.00, 0.00, 0.00) | (1.00, 0.00, 0.00) | |
| (1.00, 0.00, 0.00) | (0.66, 0.29, 0.34) | (0.71, 0.24, 0.29) | (0.70, 0.25, 0.30) | (0.67, 0.27, 0.33) | |
| (1.00, 0.00, 0.00) | (0.73, 0.23, 0.27) | (0.65, 0.30, 0.35) | (1.00, 0.00, 0.00) | (0.74, 0.21, 0.26) | |
| (0.68, 0.27, 0.32) | (0.70, 0.25, 0.30) | (0.63, 0.33, 0.37) | (1.00, 0.00, 0.00) | (0.67, 0.28, 0.33) | |
| (1.00, 0.00, 0.00) | (0.72, 0.22, 0.28) | (0.73, 0.22, 0.27) | (1.00, 0.00, 0.00) | (1.00, 0.00, 0.00) | |
| (0.69, 0.27, 0.31) | (0.66, 0.31, 0.34) | (0.68, 0.31, 0.32) | (0.70, 0.26, 0.30) | (0.79, 0.18, 0.21) | |
| (0.69, 0.26, 0.31) | (1.00, 0.00, 0.00) | (0.67, 0.28, 0.33) | (1.00, 0.00, 0.00) | (0.75, 0.20, 0.25) | |
| (0.75, 0.19, 0.25) | (0.74, 0.21, 0.26) | (0.70, 0.26, 0.30) | (0.79, 0.18, 0.21) | (0.75, 0.20, 0.25) | |
| (0.72, 0.23, 0.28) | (0.60, 0.36, 0.40) | (0.64, 0.32, 0.36) | (0.61, 0.34, 0.39) | (0.68, 0.27, 0.32) | |
| (0.64, 0.32, 0.36) | (0.64, 0.32, 0.36) | (0.65, 0.31, 0.35) | (0.64, 0.32, 0.36) | (0.67, 0.29, 0.33) | |
| (0.69, 0.25, 0.31) | (0.64, 0.32, 0.36) | (0.57, 0.40, 0.43) | (0.65, 0.31, 0.35) | (0.66, 0.29, 0.34) | |
| (0.68, 0.30, 0.32) | (0.68, 0.30, 0.32) | (0.71, 0.24, 0.29) | (0.73, 0.21, 0.27) | (0.69, 0.26, 0.31) | |
| (0.69, 0.25, 0.310 | (0.64, 0.31, 0.36) | (0.68, 0.28, 0.32) | (0.68, 0.28, 0.32) | (0.69, 0.25, 0.31) | |
| (0.68, 0.27, 0.32) | (0.63, 0.33, 0.37) | (1.00, 0.00, 0.00) | (0.64, 0.32, 0.36) | (0.66, 0.30, 0.34) | |
| (0.71, 0.23, 0.29) | (0.65, 0.31, 0.35) | (0.66, 0.29, 0.34) | (0.69, 0.27, 0.31) | (0.70, 0.25, 0.30) |
| (0.28, 0.37, 0.36) | (0.31, 0.31, 0.30) | (0.32, 0.27, 0.27) | (0.37, 0.00, 0.00) | (0.38, 0.00, 0.00) | |
| (0.29, 0.32, 0.32) | (0.43, 0.00, 0.00) | (0.43, 0.00, 0.00) | (0.26, 0.41, 0.43) | (0.28, 0.32, 0.34) | |
| (0.28, 0.34, 0.37) | (0.33, 0.24, 0.26) | (0.34, 0.22, 0.22) | (0.29, 0.26, 0.30) | (0.38, 0.00, 0.00) | |
| (0.26, 0.45, 0.46) | (0.30, 0.34, 0.34) | (0.30, 0.33, 0.34) | (0.24, 0.50, 0.49) | (0.25, 0.45, 0.44) | |
| (0.37, 0.00, 0.00) | (0.29, 0.35, 0.35) | (0.27, 0.42, 0.40) | (0.23, 0.58, 0.55) | (0.26, 0.45, 0.44) | |
| (0.27, 0.45, 0.43) | (0.27, 0.45, 0.42) | (0.30, 0.31, 0.32) | (0.37, 0.00, 0.00) | (0.38, 0.00, 0.00) | |
| (0.37, 0.00, 0.00) | (0.28, 0.37, 0.37) | (0.31, 0.30, 0.32) | (0.26, 0.41, 0.43) | (0.26, 0.43, 0.43) | |
| (0.37, 0.00, 0.00) | (0.31, 0.29, 0.30) | (0.28, 0.39, 0.38) | (0.37, 0.00, 0.00) | (0.28, 0.33, 0.35) | |
| (0.25, 0.48, 0.48) | (0.30, 0.32, 0.33) | (0.27, 0.42, 0.41) | (0.37, 0.00, 0.00) | (0.26, 0.44, 0.44) | |
| (0.37, 0.00, 0.00) | (0.31, 0.29, 0.30) | (0.31, 0.28, 0.30) | (0.37, 0.00, 0.00) | (0.38, 0.00, 0.00) | |
| (0.31, 0.32, 0.32) | (0.30, 0.33, 0.33) | (0.31, 0.34, 0.31) | (0.31, 0.31, 0.31) | (0.35, 0.22, 0.22) | |
| (0.31, 0.32, 0.32) | (0.45, 0.00, 0.00) | (0.30, 0.31, 0.32) | (0.44, 0.00, 0.00) | (0.33, 0.26, 0.27) | |
| (0.34, 0.24, 0.26) | (0.34, 0.22, 0.25) | (0.31, 0.28, 0.30) | (0.35, 0.21, 0.22) | (0.34, 0.25, 0.26) | |
| (0.33, 0.28, 0.29) | (0.27, 0.39, 0.38) | (0.29, 0.36, 0.36) | (0.27, 0.41, 0.40) | (0.30, 0.35, 0.34) | |
| (0.29, 0.39, 0.38) | (0.29, 0.35, 0.35) | (0.29, 0.34, 0.34) | (0.28, 0.39, 0.37) | (0.30, 0.36, 0.35) | |
| (0.32, 0.31, 0.32) | (0.29, 0.35, 0.34) | (0.26, 0.45, 0.42) | (0.29, 0.36, 0.36) | (0.30, 0.36, 0.36) | |
| (0.31, 0.36, 0.33) | (0.31, 0.32, 0.30) | (0.32, 0.26, 0.29) | (0.32, 0.25, 0.27) | (0.31, 0.33, 0.32) | |
| (0.32, 0.31, 0.32) | (0.29, 0.33, 0.34) | (0.31, 0.31, 0.31) | (0.30, 0.33, 0.33) | (0.31, 0.32, 0.32) | |
| (0.31, 0.32, 0.33) | (0.29, 0.35, 0.35) | (0.45, 0.00, 0.00) | (0.28, 0.38, 0.37) | (0.29, 0.37, 0.36) | |
| (0.32, 0.28, 0.30) | (0.30. 0.33, 0.33) | (0.30, 0.32, 0.33) | (0.30, 0.32, 0.32) | (0.31, 0.31, 0.32) |
| (0.02, 0.03, 0.03) | (0.04, 0.04, 0.04) | (0.05, 0.04, 0.04) | (0.06, 0.00, 0.00) | (0.04, 0.00, 0.00) | |
| (0.03, 0.03, 0.03) | (0.05, 0.00, 0.00) | (0.06, 0.00, 0.00) | (0.04, 0.06, 0.07) | (0.03, 0.04, 0.04) | |
| (0.02, 0.03, 0.03) | (0.04, 0.03, 0.03) | (0.05, 0.03, 0.03) | (0.04, 0.04, 0.05) | (0.04, 0.00, 0.00) | |
| (0.02, 0.04, 0.04) | (0.03, 0.04, 0.04) | (0.04, 0.05,0.05) | (0.04, 0.08, 0.08) | (0.03, 0.05, 0.05) | |
| (0.03, 0.00, 0.00) | (0.03, 0.04, 0.04) | (0.04, 0.06, 0.06) | (0.03, 0.09, 0.08) | (0.03, 0.05, 0.05) | |
| (0.02, 0.04, 0.04) | (0.03, 0.05, 0.05) | (0.04, 0.04, 0.05) | (0.06, 0.00, 0.00) | (0.04, 0.00, 0.00) | |
| (0.03, 0.00, 0.00) | (0.03 0.04, 0.04) | (0.04, 0.04, 0.04) | (0.04, 0.06, 0.07) | (0.03, 0.05, 0.05) | |
| (0.03, 0.00, 0.00) | (0.04, 0.03, 0.04) | (0.04, 0.05, 0.05) | (0.06, 0.00, 0.00) | (0.03, 0.04, 0.04) | |
| (0.02, 0.04, 0.04) | (0.04, 0.04, 0.04) | (0.04, 0.06, 0.06) | (0.06, 0.00, 0.00) | (0.03, 0.05, 0.05) | |
| (0.03, 0.00, 0.00) | (0.04, 0.03, 0.04) | (0.04, 0.04, 0.04) | (0.06, 0.00, 0.00) | (0.04, 0.00, 0.00) | |
| (0.02, 0.02, 0.02) | (0.03, 0.04, 0.04) | (0.02, 0.02, 0.02) | (0.03, 0.03, 0.03) | (0.02, 0.01, 0.01) | |
| (0.02, 0.02, 0.02) | (0.05, 0.00, 0.00) | (0.02, 0.02, 0.02) | (0.05, 0.00, 0.00) | (0.02, 0.01, 0.02) | |
| (0.02, 0.01, 0.01) | (0.04, 0.03, 0.03) | (0.02, 0.02, 0.02) | (0.04, 0.02, 0.02) | (0.02, 0.01, 0.01) | |
| (0.02, 0.01, 0.01) | (0.03, 0.05, 0.04) | (0.02, 0.02, 0.02) | (0.03, 0.04, 0.04) | (0.02, 0.02, 0.02) | |
| (0.01, 0.02, 0.02) | (0.03, 0.04, 0.04) | (0.02, 0.02, 0.02) | (0.03, 0.04, 0.04) | (0.02, 0.02, 0.02) | |
| (0.02, 0.02,0.02) | (0.03, 0.04, 0.04) | (0.01, 0.02, 0.02) | (0.03, 0.04, 0.04) | (0.02, 0.02, 0.02) | |
| (0.02, 0.02, 0.02) | (0.04, 0.04, 0.04) | (0.02, 0.01, 0.02) | (0.03, 0.03, 0.03) | (0.02, 0.02, 0.02) | |
| (0.02, 0.02, 0.02) | (0.03, 0.04, 0.04) | (0.02, 0.02, 0.02) | (0.03, 0.04, 0.04) | (0.02, 0.02, 0.02) | |
| (0.02, 0.02, 0.02) | (0.03, 0.04, 0.04) | (0.02, 0.00, 0.00) | (0.03, 0.04, 0.04) | (0.02, 0.02, 0.02) | |
| (0.02, 0.01, 0.01) | (0.03, 0.04, 0.04) | (0.02, 0.02, 0.02) | (0.03, 0.03, 0.03) | (0.02, 0.02, 0.02) |
| Criteria | |||||
| (0.03, 0.00, 0.00) | (0.03, 0.05, 0.05) | (0.06, 0.00, 0.00) | (0.06, 0.00, 0.00) | (0.04, 0.00, 0.00) | |
| (0.02, 0.04, 0.04) | (0.05, 0.00, 0.00) | (0.04, 0.06, 0.06) | (0.03, 0.09, 0.08) | (0.03, 0.05, 0.05) | |
| Criteria | |||||
| (0.02, 0.01, 0.01) | (0.05, 0.00, 0.00) | (0.02, 0.00, 0.00) | (0.05, 0.00, 0.00) | (0.02, 0.01, 0.01) | |
| (0.01, 0.02, 0.02) | (0.03, 0.05, 0.04) | (0.01, 0.02, 0.02) | (0.03, 0.04, 0.04) | (0.02, 0.02, 0.02) |
| 0.04 | 0.12 | 0.09 | 0.16 | 0.12 | 0.05 | 0.06 | 0.03 | 0.06 | 0.06 | 0.04 | |
| 0.05 | 0.05 | 0.14 | 0.06 | 0.06 | 0.05 | 0.12 | 0.03 | 0.11 | 0.06 | 0.05 | |
| 0.04 | 0.11 | 0.10 | 0.09 | 0.12 | 0.05 | 0.08 | 0.03 | 0.08 | 0.06 | 0.04 | |
| 0.03 | 0.12 | 0.08 | 0.05 | 0.04 | 0.05 | 0.05 | 0.03 | 0.05 | 0.06 | 0.03 | |
| 0.09 | 0.12 | 0.06 | 0.04 | 0.04 | 0.05 | 0.06 | 0.03 | 0.05 | 0.05 | 0.09 | |
| 0.03 | 0.12 | 0.08 | 0.16 | 0.12 | 0.05 | 0.06 | 0.02 | 0.05 | 0.05 | 0.03 | |
| 0.09 | 0.12 | 0.08 | 0.06 | 0.05 | 0.05 | 0.07 | 0.03 | 0.07 | 0.06 | 0.09 | |
| 0.09 | 0.11 | 0.07 | 0.16 | 0.06 | 0.05 | 0.06 | 0.03 | 0.06 | 0.06 | 0.09 | |
| 0.03 | 0.12 | 0.06 | 0.16 | 0.04 | 0.05 | 0.06 | 0.05 | 0.05 | 0.05 | 0.03 | |
| 0.09 | 0.11 | 0.09 | 0.16 | 0.12 | 0.05 | 0.06 | 0.03 | 0.06 | 0.06 | 0.09 |
| 0.09 | 0.07 | 0.14 | 0.04 | 0.04 | 0.05 | 0.12 | 0.05 | 0.11 | 0.05 | 0.09 | |
| 0.09 | 0.12 | 0.06 | 0.15 | 0.11 | 0.05 | 0.05 | 0.05 | 0.05 | 0.06 | 0.09 | |
| 0.09 | 0.08 | 0.13 | 0.15 | 0.04 | 0.05 | 0.11 | 0.05 | 0.10 | 0.06 | 0.09 | |
| 0.09 | 0.06 | 0.14 | 0.15 | 0.12 | 0.05 | 0.12 | 0.05 | 0.11 | 0.06 | 0.09 | |
| 0.03 | 0.06 | 0.14 | 0.16 | 0.12 | 0.05 | 0.12 | 0.05 | 0.11 | 0.06 | 0.03 | |
| 0.09 | 0.05 | 0.14 | 0.04 | 0.04 | 0.05 | 0.12 | 0.05 | 0.11 | 0.06 | 0.09 | |
| 0.03 | 0.06 | 0.14 | 0.15 | 0.12 | 0.05 | 0.12 | 0.05 | 0.10 | 0.06 | 0.03 | |
| 0.03 | 0.07 | 0.14 | 0.04 | 0.11 | 0.05 | 0.12 | 0.05 | 0.11 | 0.06 | 0.03 | |
| 0.09 | 0.06 | 0.14 | 0.04 | 0.12 | 0.05 | 0.12 | 0.02 | 0.11 | 0.06 | 0.09 | |
| 0.03 | 0.07 | 0.138 | 0.042 | 0.043 | 0.049 | 0.116 | 0.053 | 0.107 | 0.057 | 0.03 |
| 0.02 | 0.11 | 0.07 | 0.16 | 0.12 | 0.05 | 0.04 | 0.02 | 0.04 | 0.06 | 0.02 | |
| 0.03 | 0.03 | 0.14 | 0.03 | 0.04 | 0.05 | 0.12 | 0.02 | 0.11 | 0.06 | 0.03 | |
| 0.02 | 0.09 | 0.08 | 0.06 | 0.12 | 0.05 | 0.07 | 0.02 | 0.07 | 0.06 | 0.02 | |
| 0.02 | 0.11 | 0.05 | 0.02 | 0.02 | 0.05 | 0.03 | 0.02 | 0.03 | 0.05 | 0.02 | |
| 0.09 | 0.11 | 0.04 | 0.02 | 0.02 | 0.04 | 0.04 | 0.02 | 0.03 | 0.05 | 0.09 | |
| 0.02 | 0.12 | 0.05 | 0.16 | 0.12 | 0.05 | 0.04 | 0.01 | 0.03 | 0.05 | 0.02 | |
| 0.09 | 0.12 | 0.05 | 0.03 | 0.02 | 0.05 | 0.05 | 0.03 | 0.05 | 0.05 | 0.09 | |
| 0.09 | 0.11 | 0.04 | 0.16 | 0.04 | 0.05 | 0.04 | 0.02 | 0.04 | 0.05 | 0.09 | |
| 0.01 | 0.11 | 0.03 | 0.16 | 0.02 | 0.05 | 0.04 | 0.05 | 0.03 | 0.05 | 0.01 | |
| 0.09 | 0.10 | 0.06 | 0.16 | 0.12 | 0.05 | 0.04 | 0.02 | 0.04 | 0.05 | 0.09 |
| 0.08 | 0.05 | 0.12 | 0.02 | 0.02 | 0.05 | 0.11 | 0.05 | 0.10 | 0.05 | 0.08 | |
| 0.08 | 0.12 | 0.03 | 0.14 | 0.11 | 0.05 | 0.03 | 0.05 | 0.03 | 0.05 | 0.08 | |
| 0.08 | 0.06 | 0.11 | 0.11 | 0.02 | 0.04 | 0.10 | 0.05 | 0.08 | 0.05 | 0.08 | |
| 0.09 | 0.04 | 0.14 | 0.15 | 0.12 | 0.05 | 0.12 | 0.05 | 0.11 | 0.06 | 0.09 | |
| 0.01 | 0.04 | 0.14 | 0.16 | 0.12 | 0.05 | 0.12 | 0.05 | 0.11 | 0.06 | 0.01 | |
| 0.09 | 0.03 | 0.13 | 0.02 | 0.02 | 0.05 | 0.12 | 0.05 | 0.11 | 0.06 | 0.09 | |
| 0.01 | 0.03 | 0.13 | 0.14 | 0.12 | 0.05 | 0.11 | 0.05 | 0.10 | 0.06 | 0.01 | |
| 0.01 | 0.05 | 0.14 | 0.02 | 0.11 | 0.05 | 0.12 | 0.05 | 0.10 | 0.06 | 0.01 | |
| 0.09 | 0.04 | 0.14 | 0.02 | 0.12 | 0.05 | 0.12 | 0.01 | 0.11 | 0.06 | 0.09 | |
| 0.01 | 0.05 | 0.13 | 0.02 | 0.02 | 0.05 | 0.11 | 0.05 | 0.10 | 0.06 | 0.01 |
| Symbol | Meaning | Dimension |
|---|---|---|
| Expert rating of alternative under criterion | Linguistic term–SVNN– | |
| Truth, indeterminacy, falsity of | ||
| Weight by Entropy and DEMATEL | ||
| Hybrid weight | ||
| Aggregated values () in NTOPSIS | ||
| PIS & NIS under Neutrosophic environment | Triples ( | |
| Cosine and Jaccard Similarity measures | [0, 1] | |
| weighting parameter | [0, 1] | |
| PIS and NIS under Neutrosophic Cosine and Jaccard Similarity measures | [0, 1] | |
| Relative closeness coefficient |
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| S.no | Types of PATs | Symbol | Description |
|---|---|---|---|
| 1 | Remote Sensing | Collects information about crops and soil from a distance using satellites or aerial imagery. | |
| 2 | Global Positioning System (GPS) | Provides precise location data for field operations and mapping. | |
| 3 | Geographic Information System (GIS) | Manages and analyses spatial and geographic data for farm planning. | |
| 4 | Variable Rate Technology (VRT) | Adjusts the application of inputs, such as fertilizers and seeds, based on field variability. | |
| 5 | Soil and Crop Sensors | Measures soil properties and crop conditions in real time to support decision-making. | |
| 6 | Decision Support Systems (DSS) | Software tools that integrate data to recommend optimal farming practices. | |
| 7 | Drones/UAVs (Unmanned Aerial Vehicles) | Captures high-resolution imagery and monitor crop health efficiently. | |
| 8 | AI (Artificial Intelligence) and ML (Machine Learning)-based Precision Farming | Uses predictive models to optimize farming operations and yields. | |
| 9 | Autonomous Agricultural Machinery | Self-operating equipment for planting, harvesting, and field management. | |
| 10 | IoT (Internet of Things)-based Smart Farming | Connects sensors, devices, and systems to enable real-time farm monitoring and automation |
| S.no | Criteria | Symbol | Attribute Type | Description |
|---|---|---|---|---|
| 1 | Spatial-temporal accuracy | Benefit | Measures the precision and timeliness of information collected by technology, including location accuracy and frequency of updates. | |
| 2 | Data acquisition latency | Cost | Captures the delay between data collection and decision-making availability; lower latency is preferable. | |
| 3 | Scalability and deployability | Benefit | Reflects how easily technology can be expanded or implemented across different farm sizes and locations. | |
| 4 | Algorithmic robustness and AI integration | Benefit | Assesses the reliability and adaptability of the underlying algorithms, including integration with AI/ML models. | |
| 5 | System interoperability and data integration | Benefit | Evaluates the technology’s ability to integrate with other systems and datasets for seamless operations. | |
| 6 | Environmental resilience | Benefit | Measures the technology’s robustness to environmental conditions, including weather, soil variability, and climate. | |
| 7 | Economic feasibility and ROI (return on investment) | Benefit | Reflects cost-effectiveness, initial investment, operational costs, and expected return on investment. | |
| 8 | Automation and cognitive ergonomics | Benefit | Evaluates the level of automation and ease of use for operators, reducing human effort and cognitive load. | |
| 9 | Operational sustainability | Benefit | Assesses long-term maintainability, reliability, and efficiency of the technology in farm operations | |
| 10 | Agro-ecological impact | Benefit | Measures the positive or negative effects on soil health, biodiversity, and overall ecosystem sustainability. |
| Linguistic Variables | Single-Valued Neutrosophic Numbers (SVNNs) |
|---|---|
| Very unimportant (VU) | (0.10, 0.80, 0.90) |
| Unimportant (U) | (0.35, 0.60, 0.70) |
| Medium Important (MI) | (0.50, 0.40, 0.45) |
| Important (I) | (0.80, 0.20, 0.15) |
| Absolutely Important (AI) | (0.90, 0.10, 0.10) |
| Entropy value ( | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
| Weight () | 0.09 | 0.12 | 0.14 | 0.16 | 0.11 | 0.05 | 0.13 | 0.05 | 0.11 | 0.06 |
| Linguistic variable | High important | Medium important | High important | High important | High important |
| Weight in SVNN Scale | (0.80, 0.20, 0.15) | (0.50, 0.40, 0.45) | (0.50, 0.40, 0.45) | (0.80, 0.20, 0.15) | (0.80, 0.20, 0.15) |
| Decision makers-Weight | 0.23 | 0.16 | 0.16 | 0.23 | 0.23 |
| Alternatives | = 0 | = 0.25 | = 0.50 | = 0.75 | = 1 | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| RCC | Rank | RCC | Rank | RCC | Rank | RCC | Rank | RCC | Rank | |
| 0.51 | 2 | 0.51 | 2 | 0.51 | 2 | 0.51 | 2 | 0.51 | 2 | |
| 0.47 | 5 | 0.47 | 6 | 0.48 | 5 | 0.48 | 5 | 0.48 | 5 | |
| 0.47 | 4 | 0.47 | 4 | 0.48 | 6 | 0.48 | 6 | 0.48 | 6 | |
| 0.30 | 10 | 0.32 | 10 | 0.34 | 10 | 0.35 | 10 | 0.37 | 10 | |
| 0.35 | 9 | 0.36 | 9 | 0.38 | 9 | 0.39 | 9 | 0.40 | 9 | |
| 0.49 | 3 | 0.49 | 3 | 0.49 | 3 | 0.50 | 3 | 0.50 | 3 | |
| 0.40 | 8 | 0.41 | 8 | 0.42 | 8 | 0.43 | 8 | 0.43 | 8 | |
| 0.47 | 6 | 0.47 | 5 | 0.48 | 4 | 0.48 | 4 | 0.49 | 4 | |
| 0.43 | 7 | 0.44 | 7 | 0.44 | 7 | 0.45 | 7 | 0.46 | 7 | |
| 0.55 | 1 | 0.54 | 1 | 0.54 | 1 | 0.54 | 1 | 0.54 | 1 | |
| Alternatives | Neutrosophic Entropy-TOPSIS Method | Neutrosophic DEMATEL-TOPSIS Method | Neutrosophic (Hybrid) Entropy-DEMATEL-TOPSIS Method | |||
|---|---|---|---|---|---|---|
| RCC | Rank | RCC | Rank | RCC | Rank | |
| 0.51 | 2 | 0.51 | 2 | 0.51 | 2 | |
| 0.47 | 5 | 0.47 | 6 | 0.48 | 5 | |
| 0.47 | 6 | 0.47 | 5 | 0.48 | 6 | |
| 0.33 | 10 | 0.33 | 10 | 0.34 | 10 | |
| 0.38 | 9 | 0.37 | 9 | 0.38 | 9 | |
| 0.49 | 3 | 0.50 | 3 | 0.49 | 3 | |
| 0.42 | 8 | 0.41 | 8 | 0.42 | 8 | |
| 0.48 | 4 | 0.48 | 4 | 0.48 | 4 | |
| 0.44 | 7 | 0.45 | 7 | 0.44 | 7 | |
| 0.54 | 1 | 0.54 | 1 | 0.54 | 1 | |
| Alternatives | Base Line | Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | Scenario 5 | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| RCC | Rank | RCC | Rank | RCC | Rank | RCC | Rank | RCC | Rank | RCC | Rank | |
| 0.51 | 2 | 0.47 | 5 | 0.45 | 3 | 0.35 | 8 | 0.47 | 4 | 0.54 | 1 | |
| 0.48 | 5 | 0.58 | 1 | 0.61 | 1 | 0.60 | 1 | 0.48 | 1 | 0.51 | 3 | |
| 0.48 | 6 | 0.50 | 2 | 0.48 | 2 | 0.47 | 2 | 0.43 | 8 | 0.53 | 2 | |
| 0.34 | 10 | 0.37 | 10 | 0.31 | 10 | 0.31 | 10 | 0.39 | 10 | 0.44 | 10 | |
| 0.38 | 9 | 0.38 | 9 | 0.34 | 9 | 0.39 | 6 | 0.41 | 9 | 0.44 | 9 | |
| 0.49 | 3 | 0.47 | 4 | 0.43 | 5 | 0.36 | 7 | 0.45 | 6 | 0.46 | 7 | |
| 0.42 | 8 | 0.39 | 8 | 0.37 | 7 | 0.44 | 4 | 0.44 | 7 | 0.50 | 4 | |
| 0.48 | 4 | 0.44 | 7 | 0.38 | 6 | 0.42 | 5 | 0.46 | 5 | 0.47 | 6 | |
| 0.44 | 7 | 0.44 | 6 | 0.37 | 8 | 0.31 | 9 | 0.48 | 2 | 0.44 | 8 | |
| 0.54 | 1 | 0.49 | 3 | 0.44 | 4 | 0.46 | 3 | 0.47 | 3 | 0.47 | 5 | |
| Criteria () | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Weight () | 0.10 | 0.10 | 0.10 | 0.10 | 0.10 | 0.10 | 0.09 | 0.10 | 0.10 | 0.10 |
| Criteria’s | Weight (NEntropy) | Weight (NDEMATEL) | Hybrid Weight |
|---|---|---|---|
| 0.09 | 0.10 | 0.09 | |
| 0.12 | 0.10 | 0.12 | |
| 0.14 | 0.10 | 0.14 | |
| 0.16 | 0.10 | 0.16 | |
| 0.11 | 0.10 | 0.12 | |
| 0.05 | 0.10 | 0.05 | |
| 0.13 | 0.09 | 0.12 | |
| 0.05 | 0.10 | 0.05 | |
| 0.11 | 0.10 | 0.11 | |
| 0.06 | 0.10 | 0.06 |
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Nagari, V.P.; Subbiah, V. Geo-Information Driven Multi-Criteria Decision Analysis for Precision Agriculture Technologies Using Neutrosophic Entropy-DEMATEL and Hybrid TOPSIS. ISPRS Int. J. Geo-Inf. 2026, 15, 116. https://doi.org/10.3390/ijgi15030116
Nagari VP, Subbiah V. Geo-Information Driven Multi-Criteria Decision Analysis for Precision Agriculture Technologies Using Neutrosophic Entropy-DEMATEL and Hybrid TOPSIS. ISPRS International Journal of Geo-Information. 2026; 15(3):116. https://doi.org/10.3390/ijgi15030116
Chicago/Turabian StyleNagari, Venkata Prasanna, and Vinoth Subbiah. 2026. "Geo-Information Driven Multi-Criteria Decision Analysis for Precision Agriculture Technologies Using Neutrosophic Entropy-DEMATEL and Hybrid TOPSIS" ISPRS International Journal of Geo-Information 15, no. 3: 116. https://doi.org/10.3390/ijgi15030116
APA StyleNagari, V. P., & Subbiah, V. (2026). Geo-Information Driven Multi-Criteria Decision Analysis for Precision Agriculture Technologies Using Neutrosophic Entropy-DEMATEL and Hybrid TOPSIS. ISPRS International Journal of Geo-Information, 15(3), 116. https://doi.org/10.3390/ijgi15030116

