scholarly journals Rule-based equation for elastic tripping analysis of angle bar stiffeners

2012 ◽  
Vol 9 (2) ◽  
pp. 103-111 ◽  
Author(s):  
Ahmad Rahbar Ranji
Keyword(s):  
Energy Method ◽  
Flexural Rigidity ◽  
Torsional Rigidity ◽  
Beam Theory ◽  
Moment Of Inertia ◽  
Rule Base ◽  
Rule Based ◽  
Buckling Modes ◽  
Polar Moment ◽  
Marine Engineering

Tripping is one of buckling modes in stiffened plates which could be occurred in the stiffeners with high flexural rigidity and low torsional rigidity. Rule-base expressions for calculation of sectorial moment of inertia of angle-bar stiffeners are scattered. An expression for calculation of sectorial moment of inertia of angle-bar stiffeners is derived based on energy method and beam theory. Sectorial moment of inertia of different angle-bar stiffeners are calculated and compared with the values calculated by different classification society rules. It is found that some of the rule-based equations for calculation of sectorial moment of inertia of angle-bar stiffeners are inaccurate. Euler tripping stress of different angle bars are calculated by energy method and compared with rule-based equation and finite element method. It is found that, rule-based expression for calculation of polar moment of inertia of angle-bar stiffeners neglects one term, which could lead up to 10% overestimation of Euler tripping stress. DOI: http://dx.doi.org/10.3329/jname.v9i2.10443 Journal of Naval Architecture and Marine Engineering 9(2012) 105-111

Influence of a spanning liquid film on the stability and buckling of a circular loop with intrinsic curvature or intrinsic twist density

2016 ◽  
Vol 23 (1) ◽  
pp. 43-66 ◽  
Author(s):  
Tuan Hoang ◽  
Eliot Fried
Keyword(s):  
Surface Tension ◽  
Liquid Film ◽  
Flexural Rigidity ◽  
Torsional Rigidity ◽  
Stable Solution ◽  
Variational Model ◽  
Intrinsic Curvature ◽  
Buckling Modes ◽  
Out Of Plane ◽  
The Stability

A variational model is used to study the behavior of a flexible but inextensible loop spanned by a liquid film, with the objective of explaining the stability and buckling of flat circular configurations. Loops made from filaments with intrinsic curvature and/or intrinsic twist density are considered, but attention is restricted to filaments with circular cross sections and uniform mechanical properties. Loops made with intrinsic curvature but no intrinsic twist density exhibit in-plane and out-of-plane buckling modes corresponding to stable solution branches that bifurcate from the branch of flat circular solutions and out-of-plane buckling occurs at a lower value of the dimensionless surface tension of the liquid film than does in-plane buckling. Additionally, however, the destabilizing influence of the intrinsic curvature can be countered by increasing the torsional rigidity relative to the flexural rigidity. For a loop with both intrinsic curvature and intrinsic twist density, only one branch of stable solutions bifurcates from the flat circular solution branch, the in-plane and out-of-plane buckling modes are intertwined, and bifurcation occurs at a value of the dimensionless surface tension less than that governing the behavior of loops made from filaments that are intrinsically rectilinear. Moreover, increasing the torsional rigidity relative to the flexural rigidity has no or little stabilizing effect if the loop is either too short or too long and, in contrast to what occurs for loops with only intrinsic curvature, if the intrinsic twist density is sufficiently large then the destabilizing influence of the intrinsic curvature cannot be countered by increasing the torsional rigidity relative to the flexural rigidity, regardless of the length of the loop.

Using Gleams to Evaluate the Agricultural Waste Application Rule-Based Decision Support (AWARDS) Computer Program

1993 ◽  
Vol 28 (3-5) ◽  
pp. 625-634 ◽  
Author(s):  
D. A. Ford ◽  
A. P. Kruzic ◽  
R. L. Doneker
Keyword(s):  
Surface Water ◽  
Ground Water ◽  
Management Practices ◽  
Agricultural Waste ◽  
Rule Base ◽  
Rule Based ◽  
Pollutant Loading ◽  
Physical Features ◽  
To Receive ◽  
Complex Computer

AWARDS is a rule-based program that uses artificial intelligence techniques. It predicts the potential for fields receiving agricultural waste applications to degrade water quality. Input data required by AWARDS include the physical features, management practices, and crop nutrient needs for all fields scheduled to receive these nutrients. Based on a series of rules AWARDS analyzes the data and categorizes each field as acceptable or unacceptable for agricultural waste applications. The acceptable fields are then ranked according to their potential for pollutant loading. To evaluate the validity of the AWARDS field ranking system, it was compared to pollutant loading output from GLEAMS, a complex computer model. GLEAMS simulated the characteristics of each field ranked by AWARDS. Comparison of the AWARDS field ranking to the GLEAMS pollutant loading was favorable where ground water and both surface and ground water were to be protected and less favorable where surface water was to be protected. The rule base in AWARDS may need to be refined to provide more reasonable results where surface water is the resource of concern.

scholarly journals An Evolutionary Belief Rule-Based Clinical Decision Support System to Predict COVID-19 Severity under Uncertainty

2021 ◽  
Vol 11 (13) ◽  
pp. 5810
Author(s):  
Faisal Ahmed ◽  
Mohammad Shahadat Hossain ◽  
Raihan Ul Islam ◽  
Karl Andersson
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Experimental Result ◽  
Rule Base ◽  
Rule Based ◽  
Belief Rule Base

Accurate and rapid identification of the severe and non-severe COVID-19 patients is necessary for reducing the risk of overloading the hospitals, effective hospital resource utilization, and minimizing the mortality rate in the pandemic. A conjunctive belief rule-based clinical decision support system is proposed in this paper to identify critical and non-critical COVID-19 patients in hospitals using only three blood test markers. The experts’ knowledge of COVID-19 is encoded in the form of belief rules in the proposed method. To fine-tune the initial belief rules provided by COVID-19 experts using the real patient’s data, a modified differential evolution algorithm that can solve the constraint optimization problem of the belief rule base is also proposed in this paper. Several experiments are performed using 485 COVID-19 patients’ data to evaluate the effectiveness of the proposed system. Experimental result shows that, after optimization, the conjunctive belief rule-based system achieved the accuracy, sensitivity, and specificity of 0.954, 0.923, and 0.959, respectively, while for disjunctive belief rule base, they are 0.927, 0.769, and 0.948. Moreover, with a 98.85% AUC value, our proposed method shows superior performance than the four traditional machine learning algorithms: LR, SVM, DT, and ANN. All these results validate the effectiveness of our proposed method. The proposed system will help the hospital authorities to identify severe and non-severe COVID-19 patients and adopt optimal treatment plans in pandemic situations.

Fuzzy rule based cluster analysis to segment consumers’ preferences to eco and non-eco friendly products

2021 ◽  
Vol 24 (4) ◽  
pp. 343-351
Author(s):  
Sanjukta Ghosh ◽  
Doan Van Thang ◽  
Suresh Chandra Satapathy ◽  
Sachi Nandan Mohanty
Keyword(s):  
Fuzzy Rule ◽  
Environmental Knowledge ◽  
Purchase Behavior ◽  
Health Improvement ◽  
Rule Base ◽  
Environmental Attitude ◽  
Rule Based ◽  
Product Categories ◽  
Central Pollution Control Board ◽  
Develop Strategy

Environment protection and basic health improvement of all social communities is now considered as one of the key parameters for the development. It has become a responsibility for both industry and academia to optimize the usage of finite natural resources and preserve them. Efficient promotion and strategic marketing of Eco Friendly products can contribute to this development. It is important to consider any market as a heterogeneous mix, which requires well-organized and intelligent split or segmentation. A survey was conducted in Kolkata, metropolitan city in India, through a structured questionnaire to measure Perceived Environmental Knowledge, Perceived Environmental Attitude and Green Purchase Behavior associated to 18 product categories identified by Central Pollution Control Board for Eco Mark Scheme, 2002. Two hundred and twenty three data inputs from the respondents were analysed for this study. Here in this study a fuzzy rule based clustering technique was performed to segregate customers into two sections considering three parameters like Perceived Environmental Knowledge, Perceived Environmental Attitude and Green Purchase Behavior associated to Eco friendly product, which acts as an input variable. The rule base has linguistic variables like Significantly High, Little High, Medium, Little Low and Significantly Low and output as “Eco friendly” or “Non-ecofriendly” consumers. A set of 5×5×5= 125 rules were developed for output determination. They were designed manually and the method is applied for detection of a set of good rules. Thirteen such good rules were identified through Fuzzy Reasoning Tool, which can lead to better Decision Making and facilitate the marketers to develop strategy and take up effective marketing decisions.

scholarly journals Development of a Hybrid Electric Vehicle Simulation Tool with a Rule-Based Topology

2021 ◽  
Vol 11 (23) ◽  
pp. 11319
Author(s):  
Hyun Woo Won
Keyword(s):  
Hybrid Electric Vehicle ◽  
Hybrid Simulation ◽  
Rule Base ◽  
Simulation Tool ◽  
Control Logic ◽  
Rule Based ◽  
Vehicle Simulation ◽  
Wide Range ◽  
Hybrid Electric ◽  
And Control

The performance of hybrid electric vehicles (HEVs) greatly depends on the various sub-system components and their architecture, and designers need comprehensive reviews of HEVs before vehicle investigation and manufacturing. Simulations facilitate development of virtual prototypes that make it possible to rapidly see the effects of design modifications, avoiding the need to manufacture multiple expensive physical prototypes. To achieve the required levels of emissions and hardware costs, designers must use control strategies and tools such as computational modeling and optimization. However, most hybrid simulation tools do not share their principles and control logic algorithms in the open literature. With this motivation, the author developed a hybrid simulation tool with a rule-based topology. The major advantage of this tool is enhanced flexibility to choose different control and energy management strategies, enabling the user to explore a wide range of hybrid topologies. The tool provides the user with the ability to modify any sub-system according to one’s own requirements. In addition, the author introduces a simple logic control for a rule-base strategy as an example to show the flexibility of the tool in allowing the adaptation of any logic algorithm by the user. The results match the experimental data quite well. Details regarding modeling principle and control logic are provided for the user’s benefit.

Influence of the Torsional Rigidity of Transverse Stiffeners upon the Shear Buckling of Stiffened Plates

1964 ◽  
Vol 15 (2) ◽  
pp. 198-202 ◽  
Author(s):  
K. C. Rockey ◽  
I. T. Cook
Keyword(s):  
Flexural Rigidity ◽  
Torsional Rigidity ◽  
Stiffened Plates ◽  
Simply Supported ◽  
Rigidity Results ◽  
Buckling Resistance ◽  
Shear Buckling

SummaryThe paper provides relationships between the buckling resistance of simply-supported transversely stiffened plates and the flexural rigidity of the stiffeners for various values of the ratio of torsional rigidity to nexural rigidity. Results are presented for four different stiffener spacings.

Fuzzy Rule Interpolation

2011 ◽  
pp. 728-733 ◽  
Author(s):  
Szilveszter Kovács
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Rule ◽  
Fuzzy Reasoning ◽  
Fuzzy Relation ◽  
Rule Base ◽  
Rule Based ◽  
Fuzzy Rule Base ◽  
Current Observation ◽  
Rule Bases ◽  
Takagi Sugeno

The “fuzzy dot” (or fuzzy relation) representation of fuzzy rules in fuzzy rule based systems, in case of classical fuzzy reasoning methods (e.g. the Zadeh-Mamdani- Larsen Compositional Rule of Inference (CRI) (Zadeh, 1973) (Mamdani, 1975) (Larsen, 1980) or the Takagi - Sugeno fuzzy inference (Sugeno, 1985) (Takagi & Sugeno, 1985)), are assuming the completeness of the fuzzy rule base. If there are some rules missing i.e. the rule base is “sparse”, observations may exist which hit no rule in the rule base and therefore no conclusion can be obtained. One way of handling the “fuzzy dot” knowledge representation in case of sparse fuzzy rule bases is the application of the Fuzzy Rule Interpolation (FRI) methods, where the derivable rules are deliberately missing. Since FRI methods can provide reasonable (interpolated) conclusions even if none of the existing rules fires under the current observation. From the beginning of 1990s numerous FRI methods have been proposed. The main goal of this article is to give a brief but comprehensive introduction to the existing FRI methods.

scholarly journals A Novel Rule based Data Mining Approach towards Movie Recommender System

2020 ◽  
Vol 44 (1) ◽  
pp. 157-170
Author(s):  
Mugdha Sharma ◽  
Laxmi Ahuja ◽  
Vinay Kumar
Keyword(s):  
Recommender System ◽  
Recommendation System ◽  
Phase 1 ◽  
Research Work ◽  
Rule Learning ◽  
Rule Base ◽  
Individual Member ◽  
Phase 2 ◽  
Group Recommendation ◽  
Rule Based

The proposed research work is an effort to provide accurate movie recommendations to a group of users with the help of a rule-based content-based group recommender system. The whole approach is categorized into 2 phases. In phase 1, a rule- based approach has been proposed which considers the users’ viewing history to provide the Rule Base for every individual user. In phase 2, a novel group recommendation system has been proposed which considers the ratings of the movies as per the rule base generated in phase 1. Phase 2 also considers the weightage of every individual member of the group to provide the accurate movie recommendation to that particular group of users. The results of experimental setup also establish the fact that the proposed system provides more accurate outcomes in terms of precision and recall over other rule learning algorithms such as C4.5.

scholarly journals Compact Belief Rule Base Learning for Classification with Evidential Clustering

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 443 ◽  
Author(s):  
Lianmeng Jiao ◽  
Xiaojiao Geng ◽  
Quan Pan
Keyword(s):  
Classification System ◽  
Optimization Procedure ◽  
Classification Model ◽  
Rule Base ◽  
Data Sets ◽  
Classification Problems ◽  
Ecm Algorithm ◽  
Rule Based ◽  
Belief Rule Base ◽  
Belief Function Theory

The belief rule-based classification system (BRBCS) is a promising technique for addressing different types of uncertainty in complex classification problems, by introducing the belief function theory into the classical fuzzy rule-based classification system. However, in the BRBCS, high numbers of instances and features generally induce a belief rule base (BRB) with large size, which degrades the interpretability of the classification model for big data sets. In this paper, a BRB learning method based on the evidential C-means clustering (ECM) algorithm is proposed to efficiently design a compact belief rule-based classification system (CBRBCS). First, a supervised version of the ECM algorithm is designed by means of weighted product-space clustering to partition the training set with the goals of obtaining both good inter-cluster separability and inner-cluster pureness. Then, a systematic method is developed to construct belief rules based on the obtained credal partitions. Finally, an evidential partition entropy-based optimization procedure is designed to get a compact BRB with a better trade-off between accuracy and interpretability. The key benefit of the proposed CBRBCS is that it can provide a more interpretable classification model on the premise of comparative accuracy. Experiments based on synthetic and real data sets have been conducted to evaluate the classification accuracy and interpretability of the proposal.

Research on Rule-Based Reasoning Intelligent Selection System of Injection Mold Standard Parts

2010 ◽  
Vol 102-104 ◽  
pp. 432-435 ◽  
Author(s):  
Bai Zhong Wu ◽  
Bin Gao ◽  
Rong Song
Keyword(s):  
Rule Base ◽  
Injection Mold ◽  
Selection System ◽  
Rule Based ◽  
Standard Parts Library ◽  
Parts Library ◽  
Reasoning Mechanism ◽  
Selection Of

The use of rule-based reasoning technology can realize the intelligent selection of mold standard parts when designing injection mold. In this paper, the selection experience of mold standard parts are stored to databases for scientifically choosing mold base, sprue bushings, ejector pins, and other standard parts. And through the establishment of a rule base, reasoning mechanism, standard parts library, a rule-based reasoning intelligent selection system of injection mold standard parts is proposed and details of the proposed approach are presented.

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