scholarly journals A Selection Model on Risk Response Scheme for Complex Equipment Research and Manufacturing

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Jiao Li ◽  
Yong Liu
Keyword(s):  
Utility Theory ◽  
Group Decision ◽  
Selection Model ◽  
Cooperative Research ◽  
Risk Response ◽  
Proposed Model ◽  
Equipment Development ◽  
Complex Equipment ◽  
Group Negotiation ◽  
Scheme Selection

Risk is an important factor affecting the success of complex equipment research and manufacturing, so how to deal with the risk properly has become the key to risk management of complex equipment cooperative research and manufacturing. In view of this, considering that the choice of risk response schemes for complex equipment research and manufacturing is a consensus issue of group negotiation, this paper exploits group decision-making and utility theory to establish a risk disposal scheme selection model for complex equipment development based on group negotiation consensus, and then a case verifies the validity and rationality of the proposed model. The results show that the consensus scheme selection problem proposed in the paper effectively combines the preference value and utility, considers the supplier’s risk preference behavior, and achieves the multisubject consensus scheme.

scholarly journals A Proposed Model for Inheritance of Primocane Fruiting in Tetraploid Erect Blackberry

2000 ◽  
Vol 125 (2) ◽  
pp. 217-221 ◽  
Author(s):  
Jose Lopez-Medina ◽  
James N. Moore ◽  
Ronald W. McNew
Keyword(s):  
Negative Relationship ◽  
Recessive Gene ◽  
Segregation Ratio ◽  
Breeding Strategies ◽  
Single Recessive Gene ◽  
Tetrasomic Inheritance ◽  
Proposed Model ◽  
Inheritance Model ◽  
Diallel Crossing ◽  
Scheme Selection

Inheritance of the primocane-fruiting (PF) characteristic was studied in seedling populations of tetraploid (4x) blackberries (Rubus subgenus Rubus). Four selections (A-1836, A-593, A-830, and A-1680) and two cultivars (`Arapaho' and `Shawnee') were used as parents in a full diallel crossing scheme. Selection A-593 was used as the main source for PF due to its origin (`Brazos' × `Hillquist,' the latter an old PF cultivar). All parents except `Shawnee' have A-593 in their parentage; among the parents, only A-1836 fully expresses PF. Selfing of A-1836 resulted in 100% PF offspring, indicating that A-1836 is homozygous for this trait. Selfing of A-593, A-830, and `Arapaho' produced either a 35:1 or a 20.8:1 FF (floricane or summer-fruiting):PF segregation ratio, fitting a tetrasomic inheritance model under either random chromosome assortment (RCSA) or random chromatid assortment (RCTA), respectively, also suggesting that PF is controlled by a single recessive gene and that the parents are duplex (AAaa) for this trait. Selection A-1680 and `Shawnee' selfed did not produce PF progeny, but when crossed with the nulliplex A-1836, gave a 27:1 FF:PF ratio, indicating RCTA and that they are triplex (AAAa) for PF. According to these research, both gametic outputs (RCSA and RCTA) seem to operate in 4x blackberry. The intensity in expression of PF had a negative relationship with time to harvest, with those seedlings showing the highest PF scores producing a crop in early to mid-August. This knowledge will be helpful in implementing breeding strategies to produce PF blackberry cultivars.

Study on the Model of Individual Customer Retention in Consumer Durables Market Considering Service Input

2011 ◽  
Vol 403-408 ◽  
pp. 389-393
Author(s):  
Xu Mei Zhang ◽  
Xiang Yu Liu ◽  
Jun Li ◽  
Jie Tong
Keyword(s):  
Decision Making ◽  
Utility Theory ◽  
Customer Retention ◽  
Consumer Durables ◽  
Retention Strategy ◽  
Optimal Service ◽  
Proposed Model

Focusing on the consumer durables market, a model of individual customer retention is built based on cross-selling and utility theory considering service input. The problem of how to choose an optimal service input and corresponding retention strategy in the consumer durables market is solved by analyzing and solving of the proposed model. The validity of the model is subsequently verified through further discussion of its effect on decision making.

Constructing a Hierarchy and Simulation Model to Assess Digital Recorder Sensor System

2012 ◽  
Vol 263-266 ◽  
pp. 857-860
Author(s):  
Kuang Jung Tseng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Safety Evaluation ◽  
Decision Makers ◽  
Sensor System ◽  
Model Following ◽  
Proposed Model ◽  
Digital Recorder ◽  
Decision Making Model

This work presents group decision making model, following a university safety evaluation to demonstrate the effectiveness of the proposed model. Importantly, the proposed model can assist university decision makers to buy the feasibility of digital recorder sensor system, making it highly applicable for academic and commercial purposes.

VPRS-Based Group Decision-Making for Risk Response in Petroleum Investment

2013 ◽  
pp. 286-295
Author(s):  
Gang Xie ◽  
Wuyi Yue ◽  
Shouyang Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Project Investment ◽  
Risk Response ◽  
Multi Objective ◽  
Multi Objective Programming ◽  
Risk Indices ◽  
Multiple Risks ◽  
Future Work

From the perspective of risk response in petroleum project investment, the authors use a group decision-making (GDM) approach based on a variable precision rough set (VPRS) model for risk knowledge discovery, where experts were invited to identify risk indices and evaluate risk exposure (RE) of individual projects. First, the approach of VPRS-based GDM is introduced. Next, while considering multiple risks in petroleum project investment, the authors use multi-objective programming to obtain the optimal selection of project portfolio with minimum RE, where the significance of risk indices is assigned to each of corresponding multi-objective functions as a weight. Then, a numerical example on a Chinese petroleum company’s investments in overseas projects is presented to illustrate the proposed approach, and some important issues are analyzed. Finally, conclusions are drawn and some topics for future work are suggested.

scholarly journals A Feature Selection Model for Network Intrusion Detection System Based on PSO, GWO, FFA and GA Algorithms

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1046 ◽  
Author(s):  
Omar Almomani
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Selection Model ◽  
Network Intrusion Detection ◽  
Network Intrusion ◽  
Proposed Model ◽  
Positive Rate

The network intrusion detection system (NIDS) aims to identify virulent action in a network. It aims to do that through investigating the traffic network behavior. The approaches of data mining and machine learning (ML) are extensively used in the NIDS to discover anomalies. Regarding feature selection, it plays a significant role in improving the performance of NIDSs. That is because anomaly detection employs a great number of features that require much time. Therefore, the feature selection approach affects the time needed to investigate the traffic behavior and improve the accuracy level. The researcher of the present study aimed to propose a feature selection model for NIDSs. This model is based on the particle swarm optimization (PSO), grey wolf optimizer (GWO), firefly optimization (FFA) and genetic algorithm (GA). The proposed model aims at improving the performance of NIDSs. The proposed model deploys wrapper-based methods with the GA, PSO, GWO and FFA algorithms for selecting features using Anaconda Python Open Source, and deploys filtering-based methods for the mutual information (MI) of the GA, PSO, GWO and FFA algorithms that produced 13 sets of rules. The features derived from the proposed model are evaluated based on the support vector machine (SVM) and J48 ML classifiers and the UNSW-NB15 dataset. Based on the experiment, Rule 13 (R13) reduces the features into 30 features. Rule 12 (R12) reduces the features into 13 features. Rule 13 and Rule 12 offer the best results in terms of F-measure, accuracy and sensitivity. The genetic algorithm (GA) shows good results in terms of True Positive Rate (TPR) and False Negative Rate (FNR). As for Rules 11, 9 and 8, they show good results in terms of False Positive Rate (FPR), while PSO shows good results in terms of precision and True Negative Rate (TNR). It was found that the intrusion detection system with fewer features will increase accuracy. The proposed feature selection model for NIDS is rule-based pattern recognition to discover computer network attack which is in the scope of Symmetry journal.

Dynamic suppliers' risk management of large‐scale and complex equipment development

Kybernetes ◽  
2012 ◽  
Vol 41 (7/8) ◽  
pp. 839-850 ◽  
Author(s):  
Wenfeng Yuan ◽  
Sifeng Liu ◽  
Chaoqing Yuan
Keyword(s):  
Risk Management ◽  
Large Scale ◽  
Equipment Development ◽  
Complex Equipment

The Comprehensive Evaluation for Nuclear Facility Decommissioning Scheme Based on AHP-DEA Method

2017 ◽  
Author(s):  
Lu Bai ◽  
Yong-kuo Liu ◽  
Nan Chao
Keyword(s):  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Analytic Method ◽  
Nuclear Facility ◽  
Nuclear Facilities ◽  
Program Selection ◽  
Proposed Model ◽  
Dea Method ◽  
Scheme Selection ◽  
Selection Of

In view of the lack of research on decommissioning scheme selection of nuclear facilities and the inability to directly use the evaluation model of existing non-radioactive environment construction schemes. In this paper, propose a task analytic method in radiation field based on AHP-DEA model, which takes accomplishment the task safety as the decision-making target. The evaluation model can both reflect the decision preference of experts and improve the rationality of evaluation by mathematical calculation. The experimental results show that the proposed model has obvious advantages for program selection and can be applied to the evaluation and optimization of decommissioning scheme.

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