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.

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.

Integration of the Motor Carrier Safety Status Measurement System into the Roadside Inspection Selection System

2000 ◽  
Vol 1734 (1) ◽  
pp. 59-63
Author(s):  
Brenda M. Lantz
Keyword(s):  
Measurement System ◽  
Safety Data ◽  
Safety Performance ◽  
Similar Data ◽  
Selection System ◽  
Department Of Transportation ◽  
Commercial Vehicles ◽  
Information Systems Management ◽  
Motor Carrier ◽  
Selection Of

The roadside Inspection Selection System (ISS) was developed in response to a 1995 congressional mandate that called for the use of prior carrier safety data to guide the selection of commercial vehicles and drivers for roadside inspections. The program was developed in part by the Federal Motor Carrier Safety Administration (FMCSA) of the U.S. Department of Transportation. As ISS has developed, FMCSA’s Performance and Registration Information Systems Management (PRISM) program has also been evolving. One objective of PRISM is to identify relatively unsafe carriers by assigning Safety Status Measurement System (SafeStat) scores and also encouraging those drivers to improve their safety performance or risk losing registration privileges. SafeStat was designed to prioritize carriers for monitoring and compliance reviews, but ISS was designed to prioritize carriers for roadside inspection. Both algorithms, however, use similar data to define a relatively unsafe carrier. It would be advantageous therefore to have a single uniform rating system for all FMCSA programs. This research briefly describes the PRISM and SafeStar algorithms; discusses the integration of the SafeStat algorithm into ISS; and presents conclusions on the initial testing of the resulting system, ISS-2. An analysis of over 213,000 roadside inspections reveals that ISS-2 is as effective as the original ISS in meeting the goals for which it was designed. It successfully identifies and prioritizes for roadside inspection the vehicles and drivers of carriers with poor prior safety performance, as well as those with few or no previous inspections. In addition, safety inspectors who have tested the system say they are pleased with the new algorithm and its added features.

NX Reuse Library Workflow Based on Knowledge

2014 ◽  
Vol 687-691 ◽  
pp. 2521-2524
Author(s):  
Xiang Hui Zhan ◽  
Xiao Da Li
Keyword(s):  
Management System ◽  
Important Application ◽  
Part Family ◽  
Standard Parts Library ◽  
Standard Part ◽  
Parts Library ◽  
Reuse Library

In reuse library platform, realizing the reuse process of standard parts and common parts and building standard part management system are the important application during the whole design field. This paper introduces the method of customization standard parts library using part family, and realizes standardization management of reuse library. By creating KRX files, the knowledge components in reuse library are managed. Reuse library is an effective way to organize and use standard parts and common parts.

Rule based control of a periodic activated sludge process

1998 ◽  
Vol 38 (3) ◽  
pp. 281-289 ◽  
Author(s):  
S. Isaacs ◽  
D. Thornberg
Keyword(s):  
Dissolved Oxygen ◽  
Activated Sludge ◽  
Control Strategy ◽  
Periodic Operation ◽  
Rule Based ◽  
Criterion Functions ◽  
Strategy Performance ◽  
Working Region ◽  
And Control ◽  
Selection Of

A rule based control strategy for automatically adjusting phase lengths and aeration intensity for an activated sludge nutrient removal process based on a periodic operation is examined using simulations based on the Activated Sludge Model No. 1. The strategy is based on four criterion functions, two which determine the switching of the roles of two nitrifying/denitrifying reactors and two which adjust the dissolved oxygen setpoint levels in the two reactors as functions of ammonia and nitrate concentrations. Trajectory plots of reactor concentrations in the ammonia-nitrate plane are shown to be a useful means of visualizing process and control performance. Together, the trajectories from a working region in the ammonia-nitrate plane, the size and location of which can to some extent be predetermined by selection of the criterion functions. The presented results include the influence of one of the criterion functions on control strategy performance, how an incompatibility between two criterion functions can lead to unsymmetric reactor loading, and the effect of allowing simultaneous nitrification and denitrification during nitrifying periods by reducing the dissolved oxygen level as ammonia is consumed.

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.

Rule-Based Process Selection of Hole Making Operations for Integrated Process Planning

2005 ◽  
Author(s):  
Dusan N. Sormaz ◽  
Pravin Khurana ◽  
Ajit Wadatkar
Keyword(s):  
User Interface ◽  
Manufacturing System ◽  
Selection Procedure ◽  
Machining Process ◽  
Integrated Process ◽  
Process Selection ◽  
Rule Based ◽  
Hole Making ◽  
Significant Attention ◽  
Selection Of

Process selection as a part of CAPP has captured significant attention in CAPP research. Procedures have been developed for backward and forward algorithms in process selection. Most of these procedures lack the complete integration of process selection into CAPP system. In this paper, we present the results of the development and prototype implementation for process selection module for hole making operations for integration with Math Based Manufacturing System already in use in industrial partner. We have developed architecture and implemented module for rule-based machining process selection of hole making operations. The architecture enables the interface from the Process Selection prototype to Math Based Manufacturing System (APPS). The prototype also includes the user interface for interaction with the process selection procedure. Actions for starting prototype from APPS, performing process selection steps and sending the result back to APPS have been developed and implemented.

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