AHP/ANP theory and its application in technological and economic development: the 90th anniversary of Thomas L. Saaty

"AHP/ANP theory and its application in technological and economic development: the 90th anniversary of Thomas L. Saaty." Technological and Economic Development of Economy, 22(5), pp. 649–650 First published online: 02 Sep 201

Simulation Experiments for Improving the Consistency Ratio of Reciprocal Matrices

The consistency issue is one of the hot research topics in the analytichierarchy process (AHP) and analytic network process (ANP). To identify the mostinconsistent elements for improving the consistency ratio of a reciprocal pairwisecomparison matrix (PCM), a bias matrix can be induced to efficiently identify themost inconsistent elements, which is only based on the original PCM. The goal of thispaper is to conduct simulation experiments by randomly generating millions numbersof reciprocal matrices with different orders in order to validate the effectiveness ofthe induced bias matrix model. The experimental results show that the consistencyratios of most of the random inconsistent matrices can be improved by the inducedbias matrix model, few random inconsistent matrices with high orders failed theconsistency adjustment

Improved AHP-group decision making for investment strategy selection

Investment strategy selection relies heavily on personal experience and behavior. This paper proposes an improved Analytical Hierarchy Process-group decision making (IAHP-GDM) model to reduce investment risk. This model applies the method of least squares to adjust group decision matrix in order to satisfy the property of positive reciprocal matrix in AHP. In addition, five experts from related fields are invited to evaluate investment risk that takes group wisdom to eliminate personal bias. An empirical study is conducted to compare the proposed model to AHP for group decision making model. The results show that the IAHP-GDM model is not only accurate and effective, but also consistent with realistic investment environment

Pairwise comparison matrix in multiple criteria decision making

The measurement scales, consistency index, inconsistency issues, missing judgment estimation and priority derivation methods have been extensively studied in the pairwise comparison matrix (PCM). Various approaches have been proposed to handle these problems, and made great contributions to the decision making. This paper reviews the literature of the main developments of the PCM. There are plenty of literature related to these issues, thus we mainly focus on the literature published in 37 peer reviewed international journals from 2010 to 2015 (searched via ISI Web of science). We attempt to analyze and classify these literatures so as to find the current hot research topics and research techniques in the PCM, and point out the future directions on the PCM. It is hoped that this paper will provide a comprehensive literature review on PCM, and act as informative summary of the main developments of the PCM for the researchers for their future research. First published online: 02 Sep 201

Data Consistency in Emergency Management

Timely response is extremely important in emergency management. However, cardinal inconsistent data may exist in a judgment matrix because of the limited expertise, preference conflict as well as the complexity nature of the decision problems. The existing inconsistent data processing models for positive reciprocal matrix either are complicated or dependent on the priority weights, which will delay the decision making process in emergency. In this paper, a geometric mean induced bias matrix (GMIBM), which is only based on the original matrix A, is proposed to quickly identify the most inconsistent data in the judgment matrix. The correctness and effectiveness of the proposed model are proved mathematically and illustrated by two numerical examples. The results show that the proposed model not only preserves most of the original information in matrix A, but also is faster than existing methods

Effect of Chinese Currency Appreciation on Investments in Renewable Energy Projects in Countries along the Belt and Road

Foreign investment in renewable energy generation projects is a critical part of the Belt and Road Initiative. Under the background of the market economy, the electric energy will participate in power market competition among the countries along the line, and the sales revenue will be settled in the local currency. The exchange rate of the countries along the Belt and Road fluctuates frequently and widely, thereby posing significant risks to the investment income of the projects. To address this problem, this paper proposes the concept of Ek as the effective exchange rate expressed by the on-grid price, investment cost per kilowatt electricity generation equipment, and annual operating cost rate of unit power generation capacity. Moreover, this paper presents a model of power generation cost, income, and earning expressed by the real exchange rate. The flexibility formula of the fluctuation of power generation cost, income, profit, and internal rate of return relative(IRR) to Ek is derived, and the effect of exchange rate level and fluctuation on projects is analyzed. With the wind power projects invested by China in Pakistan taken as an example, the trend during the entire life cycle is calculated. The changes in net profit rate, IRR, and levelized cost of energy (LCOE) are calculated under Chinese currency appreciation of 10%, 20%, and 35% and 5% and 10% reduction of investment cost per unit. As the Chinese currency appreciates and the project IRR declines significantly, LCOE decreases slightly, but this decrease is not sufficient to compensate for the losses caused by the decline in IRR. The following effective measures are proposed to deal with the exchange rate fluctuation of foreign renewable energy generation projects: building energy Internet, reducing project cost, and using Chinese currency as the settlement currency. In this paper, a solution is provided for investments in renewable energy projects in regions where exchange rates fluctuate greatly

Effect of Chinese Currency Appreciation on Investments in Renewable Energy Projects in Countries along the Belt and Road

Foreign investment in renewable energy generation projects is a critical part of the Belt and Road Initiative. Under the background of the market economy, the electric energy will participate in power market competition among the countries along the line, and the sales revenue will be settled in the local currency. The exchange rate of the countries along the Belt and Road fluctuates frequently and widely, thereby posing significant risks to the investment income of the projects. To address this problem, this paper proposes the concept of Ek as the effective exchange rate expressed by the on-grid price, investment cost per kilowatt electricity generation equipment, and annual operating cost rate of unit power generation capacity. Moreover, this paper presents a model of power generation cost, income, and earning expressed by the real exchange rate. The flexibility formula of the fluctuation of power generation cost, income, profit, and internal rate of return relative(IRR) to Ek is derived, and the effect of exchange rate level and fluctuation on projects is analyzed. With the wind power projects invested by China in Pakistan taken as an example, the trend during the entire life cycle is calculated. The changes in net profit rate, IRR, and levelized cost of energy (LCOE) are calculated under Chinese currency appreciation of 10%, 20%, and 35% and 5% and 10% reduction of investment cost per unit. As the Chinese currency appreciates and the project IRR declines significantly, LCOE decreases slightly, but this decrease is not sufficient to compensate for the losses caused by the decline in IRR. The following effective measures are proposed to deal with the exchange rate fluctuation of foreign renewable energy generation projects: building energy Internet, reducing project cost, and using Chinese currency as the settlement currency. In this paper, a solution is provided for investments in renewable energy projects in regions where exchange rates fluctuate greatly

Real-Time Detection for Wheat Head Applying Deep Neural Network

Wheat head detection can estimate various wheat traits, such as density, health, and the presence of wheat head. However, traditional detection methods have a huge array of problems, including low efficiency, strong subjectivity, and poor accuracy. In this paper, a method of wheat-head detection based on a deep neural network is proposed to enhance the speed and accuracy of detection. The YOLOv4 is taken as the basic network. The backbone part in the basic network is enhanced by adding dual spatial pyramid pooling (SPP) networks to improve the ability of feature learning and increase the receptive field of the convolutional network. Multilevel features are obtained by a multipath neck part using a top-down to bottom-up strategy. Finally, YOLOv3′s head structures are used to predict the boxes of wheat heads. For training images, some data augmentation technologies are used. The experimental results demonstrate that the proposed method has a significant advantage in accuracy and speed. The mean average precision of our method is 94.5%, and the detection speed is 71 FPS that can achieve the effect of real-time detection

Mission availability for bounded-cumulative-downtime system.

In this research, a mathematics model is proposed to describe the mission availability for bounded-cumulative-downtime system. In the proposed model, the cumulative downtime and cumulative uptime are considered as constraints simultaneously. The mission availability can be defined as the probability that all repairs do not exceed the bounded cumulative downtime constraint of such system before the cumulative uptime has accrued. There are two mutually exclusive cases associated with the probability. One case is the system has not failed, where the probability can be described by system reliability. The other case is the system has failed and the cumulative downtime does not exceed the constraint before the cumulative uptime has accrued. The mathematic description of the probability under the second case is very complex. And the cumulative downtime in a mission can be set as a random variable, whose cumulative distribution means the probability that the failure system can be restored to the operating state. Giving the dependence in the scheduled mission, a mission availability model with closed form expression under this assumption is proposed. Numerical simulations are presented to illustrate the effectiveness of the proposed model. The results indicate that the relative errors are acceptable and the proposed model is effective. Furthermore, three important applications of the proposed mission availability model are discussed