Intelligent Decision Analysis Research Articles

Evaluating the Performance of Taiwan Airport Renovation Projects: An Application of Multiple Attributes Intelligent Decision Analysis

Performance evaluation is a vital tool for measuring whether construction projects meet their established objectives, particularly in complex tasks. It helps identify key areas for improvement and enhances resource allocation efficiency. Through precise performance evaluation, managers can make optimal decisions regarding resource use, ultimately increasing project productivity and overall performance. The objective of this study is to measure the production efficiency of airport renovation projects in Taiwan using data envelopment analysis (DEA) and to apply artificial neural networks (ANN) for predicting project quality. DEA effectively handles scenarios with multiple inputs and outputs, providing relative efficiency comparisons among projects and quantifying the potential for improvement. ANN, on the other hand, can learn nonlinear patterns from the data, allowing for accurate predictions of project quality. As construction projects become more complex, ensuring efficient operation within limited resources becomes increasingly crucial. Traditional performance evaluation methods are inadequate for addressing scenarios involving multiple inputs and outputs; therefore, using DEA and ANN offers a more accurate framework for analysis and prediction. The results of this study indicate that, through the DEA model, five projects achieved an efficiency score of 1, while twelve inefficient projects need to reduce defect frequency by 54.76% and increase the progress and budget implementation efficiency by an average of 10.33% to improve performance. The ANN model achieved a classification accuracy of 94.1% and a mean squared error (MSE) of 0.11 in regression predictions. By adopting a data-driven approach, ANN facilitates intelligent decision making and forecasting throughout the construction process. This study provides construction managers with concrete guidelines for resource allocation and quality prediction, thus enhancing project management effectiveness.

Applying Decision Analysis and System Dynamics Community Governance in the Evaluation of Juvenile Delinquency Prevention Strategies

Abstract From the perspective of juvenile delinquency prevention theory, this paper explores the current situation of juvenile delinquency in rural areas of W County and the mechanism of relevant functional departments in local community governance based on the questionnaire survey method. Then, six juvenile delinquency prevention service programs are selected as the object of evaluation research, and the intelligent decision analysis system of system dynamics is used as the tool of evaluation research to evaluate the six juvenile delinquency prevention programs systematically and comprehensively. The following conclusions were obtained after the analysis. The crime rate of rural youths in County W is as high as 15.8%, with a wide range of crimes. 81.6% of the relevant departments in community governance did not establish rural juvenile records, and about 13% of the departments did not conduct crime prevention training. The Green Clay People Juvenile Crime Prevention Program, which uses social connection theory as a strategy, has an evaluation value of 0.242, and the completion rate of the agreed service indicators specified in the contract is more than 100%. The overall evaluation of the six programs was 87% satisfied. Therefore, the intelligent decision analysis system in this paper has been well applied in the evaluation of juvenile crime prevention strategies, with the progress and development of society, and will occupy an important position in the future for a considerable time.

Design of enterprise human resources decision support system based on data mining

The management and development of human resources have become one of the core contents of enterprise management. It is from the initial use as an auxiliary tool in human resources business management to the later development of a relatively independent and functional sub-system for the processing of personnel matters between modules, and then to achieve the integration of various sub-systems to form a relatively complete set of human resources information management system. In recent years, with the rapid development of data mining technology, more and more enterprises have begun to attach importance to the assistance of computer information systems to manage the completion of various decision-making activities in operation. This paper designs an enterprise human resource decision support system based on data mining to more effectively support human resource management business information, data standardization, intelligent decision analysis, optimize human resource business processes, improve human resource management business efficiency, provide more effective decision support for enterprise operation and promote enterprise development. Results of the study show the effectiveness of the research.

Comprehensive Decision Analysis of Industry 4.0 Virtual Enterprises considering the Personalized Customization Model of Product Life Cycle

In the era of Industry 4.0, various types of information accumulated by enterprises in the production process have become a sea of data. These manufacturing-related data originate from enterprises and are used by enterprises and include not only process data such as documents and pictures but also complex information such as video and sound. Moreover, these data are not only large in quantity and wide in variety but also have the characteristics of fast generation speed and low value density. The model constructed in this paper can be applied to the personalized customization of product life cycle and can help enterprises make comprehensive decision-making. In particular, it can perform intelligent decision analysis under the background of Industry 4.0. In addition, this article combines intelligent algorithms to build an intelligent enterprise comprehensive decision-making system. The experimental research results show that the decision-making system proposed in this paper can play an important role in the comprehensive decision-making of Industry 4.0 enterprises, and this decision-making can be spread throughout the entire life cycle of the product.

Study on embedded system in monitoring of intelligent city pipeline network

The construction of an intelligent city needs healthy operation in all aspects. The monitoring of the intelligent city’s pipeline network in the paper is studied to ensure its healthy development. The surveillance and management system of urban underground pipeline network can improve the efficiency of network resource management, shorten the maintenance time of pipeline network, reduce the cost of resource consumption, resource management cost, and ensure the healthy operation of society. The pipeline network monitoring system is based on an embedded system, which can realize functions such as viewing, historical data query, trend analysis, alarm record query, data export, report generation, etc. The operation condition monitoring module mainly implements real-time monitoring and alarming functions for the state parameters, for example, temperature drop, pressure drop and flow velocity of each pipe section in the pipeline network, and integrates the temperature, pressure and flow data of the pipeline network and the customer terminal. The safe operation range of state parameters and alarm upper and lower lines are set by intelligent decision analysis system of pipe network and to judge the damage situation and countermeasures. The system integrates operation condition monitoring, corrosion monitoring, water hammer monitoring and other modules. Meanwhile, the monitoring interface integrates intelligent alarm and pipeline network structure information. After preliminary data processing, the system communicates with host computer data. The system also integrates the local alarm function of fault signal and valve control. Through GPRS technology as a data transmission channel and the interaction between the upper computer in the central control room and the embedded unit in the lower computer of scene. The pipeline operation parameters can be transmitted and the intelligent city pipeline network monitoring system can be realized, which plays an important role in the healthy development of the city.

Developing a Machine Vision Inspection System for Electronics Failure Analysis

Ball grid array (BGA) package components are widely used in various electronic products, as they shorten the conductive path and greatly reduce the interference during current transmission. The BGA component solder ball has little flexibility for distortion, which may cause stress concentration and solder joint cracking. Red ink dye stain analysis testing can visually analyze the cracking area and the interface of the solder joint. At present, most companies use failure analysis (FA) specialists to observe the components and circuit board end images with a microscope. As component packaging technology becomes more complex and the number of input–output (I/O) signals of the chip increases sharply, FA operations require a long time and may be misjudged due to personnel fatigue and subjective determination. This paper aims to develop a machine vision image recognition system for intelligent decision analysis to judge the severity of solder ball cracking and the cracking interface type. This system uses charge-coupled devices (CCDs) to obtain the image. First, this paper uses affine transformation compensation to perform horizontal correction, which recognizes the actual position coordinates of each solder joint, estimates the solder ball according to the Hough Circle to obtain the center and the radius of the solder ball, and then a 2-D vector map (Gerber) file is used to establish the mask, and the region of interest (ROI) in the image feature is obtained through the iterator of the pixel access program. Second, the color space is converted from red, green, and blue (RGB) to hue, saturation, and value (HSV) to reduce the effects of light variations during image capture. This paper develops the range analysis model (uses the multiple-threshold method to judge whether a particular pixel in an image has the cracking (color) feature, as well as its cracking interface), and uses a morphology filter to filter image noise (filter pixels of overlapping features). The verification results show that the system developed in this paper and FA specialists have a consistency of more than 85% in the judgment of the severity of the cracking, and the false alarm ratio and the escape ratio of the system are about 9% and 16%, respectively. Regarding the judgment result of the solder ball cracking interface type, the consistency reaches 98%, which shows that the automatic failure identification system for solder joints, as developed in this paper, can effectively assist red ink solder joint FA.

Intelligent reasoning and management decision making with grey rough influence diagrams

Purpose Influence diagrams (IDs) have been widely applied as a form of knowledge expression and a decision analysis tool in the management and engineering fields. Relationship measurements and expectation values are computed depending on probability distributions in traditional IDs, however, most information systems in the real world are nondeterministic, and data in information tables can be interval valued, multiple valued and even incomplete. Consequently, conventional numeric models of IDs are not suitable for information processing with respect to imprecise data whose boundaries are uncertain. The paper aims to discuss these issues. Design/methodology/approach The grey system theory and rough sets have proved to be effective tools in the data processing of uncertain information systems, approximate knowledge acquisition and representation are also the objectives in intelligent reasoning and decision analysis. Hence, this study proposes a new mathematical model by combining grey rough sets with IDs, and approximate measurements are used instead of probability distribution, an implicational relationship is utilized instead of an indiscernible relationship, and all of the features of the proposed approach contribute to deal with uncertain problems. Findings The focus of this paper is to provide a more comprehensive framework for approximate knowledge representation and intelligent decision analysis in uncertain information systems and an example of decision support in product management systems with the new approach is illustrated. Originality/value Collaboration of IDs and grey rough sets is first proposed, which provides a new mathematical and graphical tool for approximate reasoning and intelligent decision analysis within interval-valued information systems.

An Application Framework Design of Smart Grid IT Integrated Dispatching Operation Platform

Smart Grid construction of state grid enhanced the requirements for grid information construction, and the objective of constructing IT dispatching operation systems has been established in 12th 5-year information development plan. In order to cover every aspect of IT dispatching operation systems, including dispatching, operation, maintenance and customer service. the paper combined the advanced experience in dispatching and producing field of state grid recent years [, and with the characteristics of information field, proposed an application framework of integrated dispatching operation platform from operation layer, management layer and analysis layer to cover, in the design of operation layer, includes the contents of how to ensure rationality and security operations, in the design of management layer, includes the contents of how efficient and standardized management, in the design of analysis layer, includes the contents of how science and intelligent decision analysis. all of which ensured the efficient running of IT dispatching operation systems on the whole.