Rough-Set-Based Rule Induction with the Elimination of Outdated Big Data: Case of Renewable Energy Equipment Promotion
Abstract
:1. Introduction
- Considerations of how to handle data deletion in a Big Data system;
- An effective analysis of renewable energy data to improve the renewable energy market;
- The generation of decision rules used in an assessment scheme to promote renewable energy and proposed managerial implications.
2. Literature Review
2.1. Renewable Energy
2.2. Rough Set Theory
2.3. Research Gap
3. Solution Approach
3.1. Customer Analysis Rules
- Customer characteristic attributes are customer data that enterprises apply to customer composition analysis, such as customer type, gender and annual income.
- Government data attributes are data acquired from government agencies and integrated with customer data, such as residential electricity consumption, electricity change, regional tariff and regional payroll.
- Customer behavior and experience attributes are customer data based on customer feedback and the evaluations of their prior purchase factors.
- For the DAREA methodology, every conditional attribute is given a weight to calculate the strength index (SI), and the third-category attributes are given higher weights. Adjusting the weights is a key process of the DAREA developed in this study. The summary of all attributes is shown in Table 1.
3.2. Rule Change
3.3. Algorithms
Algorithm 1: DAREA |
Input: The number of a removed object, nd. Output: The set of decision rules and alternative rules, Fnew. Step 0. Initialization (i). When an object is removed, set the object number to be nd. (ii). Set S = 1, l = 1, Fold = original rules set, Fnew = Ø, Fgen = Ø, Fre = Ø, Fdel = Ø. Step 1. For i = 1 to q For j = 1 to r If nd ∈ D(Xi)Aj && D(Xi)Aj − nd == empty Based on Lemma 1, go to step 1.1. Else go to step 2 End If Endfor Endfor Step 1.1. Apply the reduct generation procedure of Pawlak to generate a new reduct of D(Xi)Aj. Step 1.2. Check whether the new reduct exists in the R. For i = 1 to k If the new reduct ∈ Ri Based on Lemma 2, go to step 1.2.1. Else go to step 1.2.2. End If Endfor Step 1.2.1. Add the new reduct to R. Step 1.2.2. Merge the new reduct with the identified original reduct into R. The new reduct of object number joins RMO and the cardinality is also added to ROC. Step 2. Check whether the new reduct is better than the original. For l = 1 to L If a new reduct is generated, Go to step 2.1. Else go to step 3. End If Endfor Step 2.l. Check whether the intersection of Aj and D(Xi) is empty. If it is empty Go to Step 1.1. Else go to step 2. End If Step 3. Find any reduct that is possibly affected by nd in R. For n = 1 to k If nd ∈ RMO(n) Go to step 3.1. End If Endfor Go to step 3.2. Step 3.1. When the nd is removed from RMO, subtract I(nd)OC from ROC. Step 3.2. Re-compute the strength index, SI. Sort SI according to case number, S, and Tnew is stored, with the order, for each reduct. Step 4. Check whether the new order has been changed in R. Temp = 0 For n = 1 to k If Tnew(n) != Told(n) Temp = 1 End If Endfor Step 5. Decide whether to re-extract the rules, according to the value of Temp. Based on Lemma 3, if Temp = 1, the rules must be re-extracted, so go To Step 5.1, else go To Step 6. Step 5.1. Re-extract the rules, according to AREA Set Fold = the original rules, Fgen = the new rules, Fre = the replaced rules, Fdel = the deleted rules. Step 6. Print Fnew = {Fold + Fgen + Fre − Fdel}. |
3.4. Time Complexity and Comparison
4. Case Study
4.1. Background
4.2. Data Analysis
4.3. Managerial Implication
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
U | Set of objects; |
A | Set of attributes; |
d | Set of decision attributes; |
i | Object index; |
j | Attribute index; |
n | Reduct index; |
l | Value of new level; |
L | Number of original levels; |
q | Number of object data; |
r | Number of attributes; |
k | Number of reducts in “reduct set of table”; |
S | Case number; |
Tnew | Number of sort SI according to case number S in the new reduct set of tables; |
Told | Number of sort SI according to case number S in the original reduct set of tables; |
Temp | The order number of SI that has changed and is different from the original; |
Xi | The i-th object; |
aij | The j-th value set of attributes for object Xi; |
nd | Number of removed objects; |
I() | The original information table; |
Aj | The j-th attribute; |
I(Xi)Aj | The j-th attribute for object Xi column in I, the original information table; |
D() | The difference set of each attribute Aj (the equivalent class of each object) and attribute d (the equivalent class of each object corresponding to decisive) of the table; |
D(Xi)Aj | The j-th attribute for object Xi column in the difference set; |
E | Extended table; |
R | Reduct set; |
Reductnew | The new reduct set; |
Reductold | The old reduct set; |
F | Final rule table; |
Fold | The set of rules (reducts) selected from old rules; |
Fnew | The set of rules (reducts) selected from new rules; |
Fgen | The set of rules (reducts) selected from generating rules; |
Fre | The set of rules (reducts) selected from replacing rules; |
Fdel | The set of rules (reducts) selected from new deleting rules; |
OC | Column of object cardinality; |
MO | Column of merged object; |
ROC | Index set of columns of object cardinality in the reduct set of tables; |
RMO | Index set of columns of merged object no in the reduct set of tables; |
SO | Column of support object. |
n | Total number of original objects; |
m | Total number of attributes; |
r | Total number of rules; |
q | Total number of reducts after being removed; |
k | Total number of objects after being removed; |
Ncor | Total number of original reducts from the object that generates the rule (or reduct); |
Nnr | Total number of reducts from new data set; |
Nr | Total number of rules from rule set. |
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Customer Characteristic Attributes | Government Data Attributes | Customer Behavior and Experience Attributes | Output | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Object | Gender | Age | Revenue | … | Kilowatt | Electricity Growth | … | Purchase Factors | Purchase Time | Satisfaction | Cardinality |
1 | M | 20 | 23 k | … | 200 | 1% | … | Cost | 1 year | H | 20 |
2 | F | 40 | 50 k | … | 300 | 3% | … | Environmental | 2 years | M | 15 |
3 | M | 35 | 100 k | … | 500 | −1% | … | Environmental | Over 5 years | L | 5 |
… | … | … | … | … | … | … | … | … | … | … | … |
Weight | 0.1 | 0.2 | 0.5 | … | 0.4 | 0.6 | … | 0.7 | 0.8 |
Generate New Rule | Replace Old Rule | Delete Old Rule | ||
---|---|---|---|---|
Case 1 | ---- | ---- | ---- | |
Case 2 | ---- | ---- | ✓ | |
Case 3 | ---- | ✓ | ---- | |
Case 4 | ✓ | ---- | ---- | |
Case 5 | Case 5.1 | ✓ | ✓ | ---- |
Case 5.2 | ✓ | ---- | ✓ | |
Case 5.3 | ---- | ✓ | ✓ | |
Case 5.4 | ✓ | ✓ | ✓ |
Case No. | Time Complexity |
---|---|
Case 1 | O(nm(Ncor)) |
Case 2 | O(nm(Ncor) + r(Nr)) |
Case 3 | O(nm(Ncor) + q(Nnr) + r(Nr)) |
Case 4 | O(nm(Ncor) + q(Nnr)) |
Case 5 | O(nm(Ncor) + q(Nnr) + r(Nr)) |
AREA | O(m2 k (Ncor) + qk(Nnr) + r(Nr)) |
Attribute Name | 1 | 2 | 3 | 4 | 5 | 6 | |
---|---|---|---|---|---|---|---|
A1 | Customer Type | General public | Company | Government | Other | - | - |
A2 | Gender | Male | Female | another | - | - | - |
A3 | Age | <24 | 25~34 | 35~44 | 45~54 | 55~64 | >65 |
A4 | Revenue/Year | <25 K | 26~50 | 51~75 | 76~100 | >101 | - |
A5 | Education level | Junior high | Senior high | Universities and colleges | Above | - | - |
A6 | Marital | Married | Unmarried | - | - | - | - |
A7 | Willingness | Yes | No | - | - | - | - |
A8 | Age of house | <5 | 6~30 | >30 | - | - | - |
A9 | House area (m2) | <75 | 75~200 | >201 | - | - | - |
A10 | Floors | <5 | 6~15 | >16 | - | - | - |
A11 | Area | The first three digits of the zip code | |||||
A12 | Using green power | Yes | No | - | - | - | - |
A13 | Monthly electricity consumption | <300 | 301~600 | 601~1000 | >1001 | - | - |
A14 | Average monthly electricity bill | <1000 | 1001~2000 | 2001~5000 | >5001 | - | - |
A15 | Electricity growth rate/year | <1% | 1~3% | >3% | - | - | - |
A16 | Time from the last purchase products (year) | <1 | 1~2 | 2~5 | >5 | - | - |
A17 | Product ID | The purchased product ID | |||||
A18 | Purchase intentions | Cost | Social and environmental | Brand | Policy | Other | - |
Outcome | Customer satisfaction | Very bad | Bad | Normal | Good | Very good | - |
Object | A1 | A2 | A3 | A4 | A5 | A6 | A7 | A8 | A9 | A10 | A11 | A12 | A13 | A14 | A15 | A16 | A17 | A18 | O | Cardinal Number |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 1 | 2 | 2 | 2 | 2 | 3 | 2 | 1 | 2 | 1 | 3 | 2 | 2 | 2 | 2 | 1 | 7 | 2 | 3 | 3 |
2 | 1 | 1 | 2 | 3 | 3 | 2 | 1 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 4 | 1 | 3 | 9 |
3 | 2 | 2 | 3 | 2 | 2 | 1 | 2 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 2 | 4 | 5 | 2 | 1 | 15 |
4 | 2 | 2 | 1 | 2 | 2 | 1 | 3 | 1 | 3 | 1 | 2 | 2 | 3 | 3 | 3 | 3 | 3 | 3 | 2 | 11 |
5 | 2 | 1 | 4 | 2 | 3 | 1 | 3 | 1 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 4 | 1 | 4 | 4 | 17 |
6 | 2 | 1 | 3 | 2 | 3 | 2 | 2 | 2 | 1 | 1 | 2 | 2 | 3 | 3 | 3 | 3 | 3 | 3 | 4 | 2 |
7 | 2 | 1 | 3 | 3 | 3 | 1 | 2 | 1 | 3 | 2 | 2 | 1 | 3 | 3 | 3 | 3 | 10 | 2 | 5 | 53 |
8 | 1 | 3 | 1 | 2 | 2 | 1 | 2 | 1 | 1 | 2 | 3 | 2 | 1 | 1 | 3 | 1 | 1 | 2 | 1 | 13 |
9 | 3 | 1 | 4 | 3 | 3 | 2 | 2 | 2 | 2 | 1 | 2 | 2 | 2 | 2 | 2 | 2 | 4 | 2 | 3 | 12 |
10 | 3 | 1 | 3 | 2 | 2 | 2 | 2 | 1 | 2 | 2 | 3 | 1 | 3 | 3 | 3 | 4 | 3 | 3 | 2 | 7 |
11 | 2 | 2 | 3 | 1 | 3 | 2 | 1 | 1 | 2 | 2 | 2 | 1 | 3 | 3 | 3 | 3 | 8 | 3 | 3 | 12 |
12 | 1 | 2 | 2 | 4 | 2 | 1 | 2 | 2 | 1 | 1 | 3 | 2 | 2 | 2 | 2 | 2 | 2 | 1 | 2 | 27 |
13 | 2 | 1 | 3 | 2 | 3 | 1 | 2 | 1 | 3 | 2 | 3 | 2 | 3 | 3 | 3 | 4 | 3 | 3 | 5 | 22 |
14 | 4 | 2 | 1 | 2 | 3 | 1 | 2 | 1 | 3 | 2 | 3 | 1 | 3 | 3 | 3 | 3 | 9 | 4 | 4 | 8 |
15 | 2 | 3 | 2 | 1 | 3 | 2 | 1 | 1 | 2 | 1 | 3 | 2 | 3 | 3 | 3 | 3 | 6 | 3 | 2 | 11 |
…… | ||||||||||||||||||||
500 | 1 | 2 | 3 | 5 | 2 | 1 | 4 | 2 | 3 | 3 | 2 | 1 | 3 | 4 | 2 | 2 | 7 | 2 | 4 | 6 |
wj | 0.75 | 0.28 | 0.75 | 0.92 | 0.61 | 0.25 | 0.67 | 0.65 | 0.6 | 0.4 | 0.65 | 0.67 | 0.82 | 0.81 | 0.79 | 0.32 | 1.0 | 0.91 |
Rule | A1 | A2 | A3 | A4 | A5 | A6 | A7 | A8 | A9 | A10 | A11 | A12 | A13 | A14 | A15 | A16 | A17 | A18 | O |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 1 | 1 | 2 | 1 | 2 | 5 | |||||||||||||
2 | 3 | 1 | 1 | 1 | 2 | 5 | |||||||||||||
3 | 2 | 3 | 3 | 106 | 9 | 1 | 3 | ||||||||||||
4 | 1 | 3 | 1 | 4 | 8 | 1 | |||||||||||||
5 | 2 | 4 | 2 | 4 | 1 | ||||||||||||||
6 | 2 | 5 | 110 | 4 | 4 | 8 | 5 | ||||||||||||
7 | 1 | 2 | 1 | 2 | 1 | 4 | |||||||||||||
8 | 3 | 3 | 4 | 1 | 2 | 4 | |||||||||||||
9 | 2 | 2 | 3 | 3 | 12 | 5 | |||||||||||||
10 | 3 | 2 | 2 | 3 | 3 | 2 | |||||||||||||
11 | 4 | 2 | 1 | 4 | 3 | ||||||||||||||
12 | 2 | 3 | 1 | 2 | 4 | 4 | |||||||||||||
13 | 1 | 1 | 1 | 8 | 1 | 5 | |||||||||||||
14 | 2 | 1 | 2 | 9 | 3 | ||||||||||||||
15 | 1 | 3 | 2 | 1 | 3 | 4 | |||||||||||||
…. |
Object | A1 | A2 | A3 | A4 | A5 | A6 | A7 | A8 | A9 | A10 | A11 | A12 | A13 | A14 | A15 | A16 | A17 | A18 | O | Cardinal Number |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 1 | 2 | 2 | 2 | 2 | 3 | 2 | 1 | 2 | 1 | 3 | 2 | 2 | 2 | 2 | 1 | 7 | 2 | 3 | 3 |
2 | 1 | 1 | 2 | 3 | 3 | 2 | 1 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 4 | 1 | 3 | 9 |
3 | 2 | 2 | 3 | 2 | 2 | 1 | 2 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 2 | 4 | 8 | 2 | 1 | 15 |
4 | 2 | 2 | 1 | 2 | 2 | 1 | 3 | 1 | 3 | 1 | 2 | 2 | 3 | 3 | 3 | 3 | 3 | 3 | 2 | 11 |
5 | 2 | 1 | 4 | 2 | 3 | 1 | 3 | 1 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 4 | 1 | 4 | 4 | 17 |
6 | 2 | 1 | 3 | 2 | 3 | 2 | 2 | 2 | 1 | 1 | 2 | 2 | 3 | 3 | 3 | 3 | 3 | 3 | 4 | 2 |
7 | 2 | 1 | 3 | 3 | 3 | 1 | 2 | 1 | 3 | 2 | 2 | 1 | 3 | 3 | 3 | 3 | 10 | 2 | 5 | 53 |
8 | 1 | 3 | 1 | 2 | 2 | 1 | 2 | 1 | 1 | 2 | 3 | 2 | 1 | 1 | 3 | 1 | 1 | 2 | 1 | 13 |
9 | 3 | 1 | 4 | 3 | 3 | 2 | 2 | 2 | 2 | 1 | 2 | 2 | 2 | 2 | 2 | 2 | 4 | 2 | 3 | 12 |
10 | 3 | 1 | 3 | 2 | 2 | 2 | 2 | 1 | 2 | 2 | 3 | 1 | 3 | 3 | 3 | 4 | 3 | 3 | 2 | 7 |
11 | 2 | 2 | 3 | 1 | 3 | 2 | 1 | 1 | 2 | 2 | 2 | 1 | 3 | 3 | 3 | 3 | 8 | 3 | 3 | 12 |
12 | 1 | 2 | 2 | 4 | 2 | 1 | 2 | 2 | 1 | 1 | 3 | 2 | 2 | 2 | 2 | 2 | 2 | 1 | 2 | 27 |
13 | 2 | 1 | 3 | 2 | 3 | 1 | 2 | 1 | 3 | 2 | 3 | 2 | 3 | 3 | 3 | 4 | 3 | 3 | 5 | 22 |
14 | 4 | 2 | 1 | 2 | 3 | 1 | 2 | 1 | 3 | 2 | 3 | 1 | 3 | 3 | 3 | 3 | 9 | 4 | 4 | 8 |
15 | 2 | 3 | 2 | 1 | 3 | 2 | 1 | 1 | 2 | 1 | 3 | 2 | 3 | 3 | 3 | 3 | 6 | 3 | 2 | 11 |
…… | ||||||||||||||||||||
500 | 1 | 2 | 3 | 5 | 2 | 1 | 4 | 2 | 3 | 3 | 2 | 1 | 3 | 4 | 2 | 2 | 7 | 2 | 4 | 6 |
wj | 0.33 | 0.28 | 0.75 | 0.88 | 0.61 | 0.25 | 0.67 | 0.65 | 0.6 | 0.4 | 0.85 | 0.67 | 0.92 | 0.81 | 0.79 | 0.32 | 1.0 | 0.62 |
Object | A1 | A2 | A3 | A4 | A5 | A6 | A7 | A8 | A9 | A10 | A11 | A12 | A13 | A14 | A15 | A16 | A17 | A18 | O | Cardinal Number |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 1 | 2 | 2 | 2 | 2 | 3 | 2 | 1 | 2 | 1 | 3 | 2 | 2 | 2 | 2 | 1 | 7 | 2 | 3 | 3 |
2 | 1 | 1 | 2 | 3 | 3 | 2 | 1 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 4 | 1 | 3 | 9 |
3 | 2 | 2 | 1 | 2 | 2 | 1 | 3 | 1 | 3 | 1 | 2 | 2 | 3 | 3 | 3 | 3 | 3 | 3 | 2 | 11 |
4 | 2 | 1 | 3 | 2 | 3 | 2 | 2 | 2 | 1 | 1 | 2 | 2 | 3 | 3 | 3 | 3 | 3 | 3 | 4 | 2 |
5 | 2 | 1 | 3 | 3 | 3 | 1 | 2 | 1 | 3 | 2 | 2 | 1 | 3 | 3 | 3 | 3 | 10 | 2 | 5 | 53 |
6 | 1 | 3 | 1 | 2 | 2 | 1 | 2 | 1 | 1 | 2 | 3 | 2 | 1 | 1 | 3 | 1 | 1 | 2 | 1 | 13 |
7 | 3 | 1 | 4 | 3 | 3 | 2 | 2 | 2 | 2 | 1 | 2 | 2 | 2 | 2 | 2 | 2 | 4 | 2 | 3 | 12 |
8 | 2 | 2 | 3 | 1 | 3 | 2 | 1 | 1 | 2 | 2 | 2 | 1 | 3 | 3 | 3 | 3 | 8 | 3 | 3 | 12 |
9 | 1 | 2 | 2 | 4 | 2 | 1 | 2 | 2 | 1 | 1 | 3 | 2 | 2 | 2 | 2 | 2 | 2 | 1 | 2 | 27 |
10 | 4 | 2 | 1 | 2 | 3 | 1 | 2 | 1 | 3 | 2 | 3 | 1 | 3 | 3 | 3 | 3 | 9 | 4 | 4 | 8 |
11 | 2 | 3 | 2 | 1 | 3 | 2 | 1 | 1 | 2 | 1 | 3 | 2 | 3 | 3 | 3 | 3 | 6 | 3 | 2 | 11 |
…… | ||||||||||||||||||||
430 | 1 | 2 | 3 | 5 | 2 | 1 | 4 | 2 | 3 | 3 | 2 | 1 | 3 | 4 | 2 | 2 | 7 | 2 | 4 | 6 |
wj | 0.75 | 0.28 | 0.75 | 0.92 | 0.61 | 0.25 | 0.67 | 0.65 | 0.6 | 0.4 | 0.85 | 0.67 | 0.92 | 0.81 | 0.79 | 0.32 | 1.0 | 0.62 |
Rule | A1 | A2 | A3 | A4 | A5 | A6 | A7 | A8 | A9 | A10 | A11 | A12 | A13 | A14 | A15 | A16 | A17 | A18 | O |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 1 | 1 | 2 | 1 | 2 | 5 | |||||||||||||
2 | 3 | 1 | 1 | 1 | 2 | 5 | |||||||||||||
3 | 2 | 3 | 3 | 106 | 9 | 1 | 3 | ||||||||||||
4 | 1 | 3 | 1 | 4 | 8 | 1 | |||||||||||||
5 | 2 | 4 | 2 | 4 | 1 | ||||||||||||||
6 | 2 | 5 | 110 | 4 | 4 | 8 | 5 | ||||||||||||
7 | 1 | 2 | 1 | 2 | 1 | 4 | |||||||||||||
8 | 3 | 3 | 4 | 1 | 2 | 4 | |||||||||||||
9 | 2 | 2 | 3 | 3 | 12 | 5 | |||||||||||||
10 | 3 | 2 | 2 | 3 | 3 | 2 | |||||||||||||
11 | 4 | 2 | 1 | 4 | 3 | ||||||||||||||
12 | 2 | 3 | 1 | 2 | 4 | 4 | |||||||||||||
13 | 1 | 1 | 1 | 8 | 1 | 5 | |||||||||||||
14 | 2 | 1 | 2 | 9 | 3 | ||||||||||||||
15 | 1 | 3 | 2 | 1 | 3 | 4 | |||||||||||||
…. |
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Huang, C.-C.; Liang, W.-Y.; Gung, R.R.; Wang, P.-A. Rough-Set-Based Rule Induction with the Elimination of Outdated Big Data: Case of Renewable Energy Equipment Promotion. Sustainability 2023, 15, 14984. https://doi.org/10.3390/su152014984
Huang C-C, Liang W-Y, Gung RR, Wang P-A. Rough-Set-Based Rule Induction with the Elimination of Outdated Big Data: Case of Renewable Energy Equipment Promotion. Sustainability. 2023; 15(20):14984. https://doi.org/10.3390/su152014984
Chicago/Turabian StyleHuang, Chun-Che, Wen-Yau Liang, Roger R. Gung, and Pei-An Wang. 2023. "Rough-Set-Based Rule Induction with the Elimination of Outdated Big Data: Case of Renewable Energy Equipment Promotion" Sustainability 15, no. 20: 14984. https://doi.org/10.3390/su152014984
APA StyleHuang, C. -C., Liang, W. -Y., Gung, R. R., & Wang, P. -A. (2023). Rough-Set-Based Rule Induction with the Elimination of Outdated Big Data: Case of Renewable Energy Equipment Promotion. Sustainability, 15(20), 14984. https://doi.org/10.3390/su152014984