 | 2012 |
| 22 |  | Min-Yuan Cheng,
Yu-Wei Wu:
Improved Construction Subcontractor Evaluation Performance Using ESIM.
Applied Artificial Intelligence 26(3): 261-273 (2012) |
| 21 |  | Min-Yuan Cheng,
Nhat-Duc Hoang,
Andreas F. V. Roy,
Yu-Wei Wu:
A novel time-depended evolutionary fuzzy SVM inference model for estimating construction project at completion.
Eng. Appl. of AI 25(4): 744-752 (2012) |
| 20 |  | Min-Yuan Cheng,
Li-Chuan Lien:
A hybrid AI-based particle bee algorithm for facility layout optimization.
Eng. Comput. (Lond.) 28(1): 57-69 (2012) |
| 19 |  | Li-Chuan Lien,
Min-Yuan Cheng:
A hybrid swarm intelligence based particle-bee algorithm for construction site layout optimization.
Expert Syst. Appl. 39(10): 9642-9650 (2012) |
| 18 |  | Min-Yuan Cheng,
Andreas F. V. Roy,
Kuan-Lin Chen:
Evolutionary risk preference inference model using fuzzy support vector machine for road slope collapse prediction.
Expert Syst. Appl. 39(2): 1737-1746 (2012) |
| 17 |  | Ching-Shan Chen,
Min-Yuan Cheng,
Yu-Wei Wu:
Seismic assessment of school buildings in Taiwan using the evolutionary support vector machine inference system.
Expert Syst. Appl. 39(4): 4102-4110 (2012) |
| 16 |  | Tao Sun,
Woo-Tae Park,
Min-Yuan Cheng,
Jing-Zhi An,
Rui-Feng Xue,
Kwan-Ling Tan,
Minkyu Je:
Implantable Polyimide Cable for Multichannel High-Data-Rate Neural Recording Microsystems.
IEEE Trans. Biomed. Engineering 59(2): 390-399 (2012) |
| 15 |  | Min-Yuan Cheng,
Kuo-Yu Huang,
Hung-Ming Chen:
Dynamic guiding particle swarm optimization with embedded chaotic search for solving multidimensional problems.
Optimization Letters 6(4): 719-729 (2012) |
| 2011 |
| 14 |  | Min-Yuan Cheng,
Hsing-Chih Tsai,
Kai-Hsiang Chuang:
Supporting international entry decisions for construction firms using fuzzy preference relations and cumulative prospect theory.
Expert Syst. Appl. 38(12): 15151-15158 (2011) |
| 13 |  | Min-Yuan Cheng,
Hsien-Sheng Peng,
Yu-Wei Wu,
Yi-Hung Liao:
Decision making for contractor insurance deductible using the evolutionary support vector machines inference model.
Expert Syst. Appl. 38(6): 6547-6555 (2011) |
| 12 |  | Jui-Sheng Chou,
Min-Yuan Cheng,
Yu-Wei Wu,
Yian Tai:
Predicting high-tech equipment fabrication cost with a novel evolutionary SVM inference model.
Expert Syst. Appl. 38(7): 8571-8579 (2011) |
| 2010 |
| 11 |  | Min-Yuan Cheng,
Hsing-Chih Tsai,
Erick Sudjono:
Evolutionary fuzzy hybrid neural network for project cash flow control.
Eng. Appl. of AI 23(4): 604-613 (2010) |
| 10 |  | Min-Yuan Cheng,
Hsing-Chih Tsai,
Erick Sudjono:
Conceptual cost estimates using evolutionary fuzzy hybrid neural network for projects in construction industry.
Expert Syst. Appl. 37(6): 4224-4231 (2010) |
| 9 |  | Min-Yuan Cheng,
Andreas F. V. Roy:
Evolutionary fuzzy decision model for construction management using support vector machine.
Expert Syst. Appl. 37(8): 6061-6069 (2010) |
| 2009 |
| 8 |  | Min-Yuan Cheng,
Hsing-Chih Tsai,
Yi-Hsiang Chiu:
Fuzzy case-based reasoning for coping with construction disputes.
Expert Syst. Appl. 36(2): 4106-4113 (2009) |
| 7 |  | Min-Yuan Cheng,
Chin-Jung Huang:
A Novel Approach for Treating Uncertain Rule-based Knowledge Conflicts.
J. Inf. Sci. Eng. 25(2): 649-663 (2009) |
| 2008 |
| 6 |  | Min-Yuan Cheng,
Chin-Jung Huang:
Value-added treatment inference model for rule-based certainty knowledge.
Expert Syst. Appl. 34(2): 1250-1265 (2008) |
| 5 |  | Chin-Jung Huang,
Min-Yuan Cheng:
Conflicting treatment model for certainty rule-based knowledge.
Expert Syst. Appl. 35(1-2): 161-176 (2008) |
| 4 |  | Chin-Jung Huang,
Min-Yuan Cheng:
Similarity Measurement of Rule-based Knowledge using Conditional Probability.
J. Inf. Sci. Eng. 24(3): 769-784 (2008) |
| 2006 |
| 3 |  | Chin-Jung Huang,
Min-Yuan Cheng:
Using Conditional Probability to Measure Rule-based Knowledge Similarity.
SEKE 2006: 41-44 |
| 2 |  | Chin-Jung Huang,
Min-Yuan Cheng:
A New Method of Value-Adding Treatment Inference for Rule-based Uncertainty Knowledge.
SEKE 2006: 51-56 |
| 1 |  | Min-Yuan Cheng,
Chien-Ho Ko:
A genetic-fuzzy-neuro model encodes FNNs using SWRM and BRM.
Eng. Appl. of AI 19(8): 891-903 (2006) |