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Abstract

Details

The Theory of Monetary Aggregation
Type: Book
ISBN: 978-0-44450-119-6

Abstract

Details

The Theory of Monetary Aggregation
Type: Book
ISBN: 978-0-44450-119-6

Book part
Publication date: 5 October 2018

Nasir Bedewi Siraj, Aminah Robinson Fayek and Mohamed M. G. Elbarkouky

Most decision-making problems in construction are complex and difficult to solve, as they involve multiple criteria and multiple decision makers in addition to subjective…

Abstract

Most decision-making problems in construction are complex and difficult to solve, as they involve multiple criteria and multiple decision makers in addition to subjective uncertainties, imprecisions and vagueness surrounding the decision-making process. In many instances, the decision-making process is based on linguistic terms rather than numerical values. Hence, structured fuzzy consensus-reaching processes and fuzzy aggregation methods are instrumental in multi-criteria group decision-making (MCGDM) problems for capturing the point of view of a group of experts. This chapter outlines different fuzzy consensus-reaching processes and fuzzy aggregation methods. It presents the background of the basic theory and formulation of these processes and methods, as well as numerical examples that illustrate their theory and formulation. Application areas of fuzzy consensus reaching and fuzzy aggregation in the construction domain are identified, and an overview of previously developed frameworks for fuzzy consensus reaching and fuzzy aggregation is provided. Finally, areas for future work are presented that highlight emerging trends and the imminent needs of fuzzy consensus reaching and fuzzy aggregation in the construction domain.

Details

Fuzzy Hybrid Computing in Construction Engineering and Management
Type: Book
ISBN: 978-1-78743-868-2

Keywords

Article
Publication date: 17 February 2022

Prajakta Thakare and Ravi Sankar V.

Agriculture is the backbone of a country, contributing more than half of the sector of economy throughout the world. The need for precision agriculture is essential in…

Abstract

Purpose

Agriculture is the backbone of a country, contributing more than half of the sector of economy throughout the world. The need for precision agriculture is essential in evaluating the conditions of the crops with the aim of determining the proper selection of pesticides. The conventional method of pest detection fails to be stable and provides limited accuracy in the prediction. This paper aims to propose an automatic pest detection module for the accurate detection of pests using the hybrid optimization controlled deep learning model.

Design/methodology/approach

The paper proposes an advanced pest detection strategy based on deep learning strategy through wireless sensor network (WSN) in the agricultural fields. Initially, the WSN consisting of number of nodes and a sink are clustered as number of clusters. Each cluster comprises a cluster head (CH) and a number of nodes, where the CH involves in the transfer of data to the sink node of the WSN and the CH is selected using the fractional ant bee colony optimization (FABC) algorithm. The routing process is executed using the protruder optimization algorithm that helps in the transfer of image data to the sink node through the optimal CH. The sink node acts as the data aggregator and the collection of image data thus obtained acts as the input database to be processed to find the type of pest in the agricultural field. The image data is pre-processed to remove the artifacts present in the image and the pre-processed image is then subjected to feature extraction process, through which the significant local directional pattern, local binary pattern, local optimal-oriented pattern (LOOP) and local ternary pattern (LTP) features are extracted. The extracted features are then fed to the deep-convolutional neural network (CNN) in such a way to detect the type of pests in the agricultural field. The weights of the deep-CNN are tuned optimally using the proposed MFGHO optimization algorithm that is developed with the combined characteristics of navigating search agents and the swarming search agents.

Findings

The analysis using insect identification from habitus image Database based on the performance metrics, such as accuracy, specificity and sensitivity, reveals the effectiveness of the proposed MFGHO-based deep-CNN in detecting the pests in crops. The analysis proves that the proposed classifier using the FABC+protruder optimization-based data aggregation strategy obtains an accuracy of 94.3482%, sensitivity of 93.3247% and the specificity of 94.5263%, which is high as compared to the existing methods.

Originality/value

The proposed MFGHO optimization-based deep-CNN is used for the detection of pest in the crop fields to ensure the better selection of proper cost-effective pesticides for the crop fields in such a way to increase the production. The proposed MFGHO algorithm is developed with the integrated characteristic features of navigating search agents and the swarming search agents in such a way to facilitate the optimal tuning of the hyperparameters in the deep-CNN classifier for the detection of pests in the crop fields.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

Open Access
Article
Publication date: 7 June 2021

Gregory S. Cooper, Karl M. Rich, Bhavani Shankar and Vinay Rana

Agricultural aggregation schemes provide numerous farmer-facing benefits, including reduced transportation costs and improved access to higher-demand urban markets…

1086

Abstract

Purpose

Agricultural aggregation schemes provide numerous farmer-facing benefits, including reduced transportation costs and improved access to higher-demand urban markets. However, whether aggregation schemes also have positive food security dimensions for consumers dependent on peri-urban and local markets in developing country contexts is currently unknown. This paper aims to narrow this knowledge gap by exploring the actors, governance structures and physical infrastructures of the horticultural value chain of Bihar, India, to identify barriers to using aggregation to improve the distribution of fruits and vegetables to more local market environments.

Design/methodology/approach

This study uses mixed methods. Quantitative analysis of market transaction data explores the development of aggregation supply pathways over space and time. In turn, semi-structured interviews with value chain actors uncover the interactions and decision-making processes with implications for equitable fruit and vegetable delivery.

Findings

Whilst aggregation successfully generates multiple producer-facing benefits, the supply pathways tend to cluster around urban export-oriented hubs, owing to the presence of high-capacity traders, large consumer bases and traditional power dynamics. Various barriers across the wider enabling environment must be overcome to unlock the potential for aggregation to increase local fruit and vegetable delivery, including informal governance structures, cold storage gaps and underdeveloped transport infrastructures.

Originality/value

To the best of the authors’ knowledge, this study is the first critical analysis of horticultural aggregation through a consumer-sensitive lens. The policy-relevant lessons are pertinent to the equitable and sustainable development of horticultural systems both in Bihar and in similar low- and middle-income settings.

Details

Journal of Agribusiness in Developing and Emerging Economies, vol. 12 no. 2
Type: Research Article
ISSN: 2044-0839

Keywords

Content available
Article
Publication date: 10 May 2021

Zachary Hornberger, Bruce Cox and Raymond R. Hill

Large/stochastic spatiotemporal demand data sets can prove intractable for location optimization problems, motivating the need for aggregation. However, demand aggregation

Abstract

Purpose

Large/stochastic spatiotemporal demand data sets can prove intractable for location optimization problems, motivating the need for aggregation. However, demand aggregation induces errors. Significant theoretical research has been performed related to the modifiable areal unit problem and the zone definition problem. Minimal research has been accomplished related to the specific issues inherent to spatiotemporal demand data, such as search and rescue (SAR) data. This study provides a quantitative comparison of various aggregation methodologies and their relation to distance and volume based aggregation errors.

Design/methodology/approach

This paper introduces and applies a framework for comparing both deterministic and stochastic aggregation methods using distance- and volume-based aggregation error metrics. This paper additionally applies weighted versions of these metrics to account for the reality that demand events are nonhomogeneous. These metrics are applied to a large, highly variable, spatiotemporal demand data set of SAR events in the Pacific Ocean. Comparisons using these metrics are conducted between six quadrat aggregations of varying scales and two zonal distribution models using hierarchical clustering.

Findings

As quadrat fidelity increases the distance-based aggregation error decreases, while the two deliberate zonal approaches further reduce this error while using fewer zones. However, the higher fidelity aggregations detrimentally affect volume error. Additionally, by splitting the SAR data set into training and test sets this paper shows the stochastic zonal distribution aggregation method is effective at simulating actual future demands.

Originality/value

This study indicates no singular best aggregation method exists, by quantifying trade-offs in aggregation-induced errors practitioners can utilize the method that minimizes errors most relevant to their study. Study also quantifies the ability of a stochastic zonal distribution method to effectively simulate future demand data.

Details

Journal of Defense Analytics and Logistics, vol. 5 no. 1
Type: Research Article
ISSN: 2399-6439

Keywords

Article
Publication date: 5 June 2017

Anthony Owusu-Ansah, William Mark Adolwine and Eric Yeboah

The purpose of this paper is to test whether temporal aggregation matters when constructing hedonic house price indices for developing markets using Ghana as a case study.

Abstract

Purpose

The purpose of this paper is to test whether temporal aggregation matters when constructing hedonic house price indices for developing markets using Ghana as a case study.

Design/methodology/approach

Monthly, quarterly, semi-yearly and yearly hedonic price indices are constructed and six null hypotheses are tested using the F-ratios to examine the temporal aggregation effect.

Findings

The results show that temporal aggregation may not be a serious issue when constructing hedonic house price indices for developing markets as a result of the smaller sample size which these markets normally have. At even 10 per cent significance level, none of the F-ratios estimated is statistically significant. Analysis of the mean returns and volatilities reveal that indices constructed at the lower level of temporal aggregation are very volatile, suggesting that the volume of transactions can affect the level of temporal aggregation, and so, the temporal aggregation level should not be generalised, as is currently observed in the literature.

Originality/value

The diversification importance of real estate and the introduction of real estate derivatives and home equity insurance as financial products call for the construction of robust and accurate real estate indices in all markets. While almost all empirical research recommends real estate price indices to be conducted at the lower level of temporal aggregation, these studies are largely conducted in developed markets where transactions take place frequently and large transaction databases exist. Unfortunately, little is known about the importance of temporal aggregation effect when constructing indices for developing real estate markets. This paper contributes to fill these gaps.

Details

International Journal of Housing Markets and Analysis, vol. 10 no. 3
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 29 March 2013

Anthony Owusu‐Ansah

The purpose of this paper is to examine if temporal aggregation matters in the construction of house price indices and to test the accuracy of alternative index…

Abstract

Purpose

The purpose of this paper is to examine if temporal aggregation matters in the construction of house price indices and to test the accuracy of alternative index construction methods.

Design/methodology/approach

Five index construction models based on the hedonic, repeat‐sales and hybrid methods are examined. The accuracy of the alternative index construction methods are examined using the mean squared error and out‐of‐sample technique. Monthly, quarterly, semi‐yearly and yearly indices are constructed for each of the methods and six null hypotheses are tested to examine the temporal aggregation effect.

Findings

Overall, the hedonic is the best method to use. While running separate regressions to estimate the index is best at the broader level of time aggregation like the annual, pooling data together and including time dummies to estimate the index is the best at the lower level of time aggregation. The repeat‐sales method is the least preferred method. The results also show that it is important to limit time to the lowest level of temporal aggregation when construction property price indices.

Practical implications

This paper provides alternative method, the mean squared error method based on an out‐of‐sample technique to evaluate the accuracy of alternative index construction methods.

Originality/value

The introduction of financial products like the property derivatives and home equity insurances to the financial market calls for accurate and robust property price indices. However, the index method and level of temporal aggregation to use still remain unresolved in the index construction literature. This paper contributes to fill these gaps.

Details

Property Management, vol. 31 no. 2
Type: Research Article
ISSN: 0263-7472

Keywords

Article
Publication date: 1 February 2006

Mark Matthews

The purpose of this article is to examine the progress of account aggregation, the means by which consumers can view all their online banking accounts on the same PC screen.

831

Abstract

Purpose

The purpose of this article is to examine the progress of account aggregation, the means by which consumers can view all their online banking accounts on the same PC screen.

Design/methodology/approach

The study looks at the examples of several online banks and their experiences.

Findings

The article finds that account aggregation is very much in its infancy with banks still only on the brink of really exploiting the customer data that account aggregation can provide. It also discovers that, rather than being viewed as a standalone product, it looks as if account aggregation could involve added value services such as enhanced customer security, electronic bill payment and personal cash management services.

Originality/value

This article provides a useful insight into the development of account aggregation.

Details

International Journal of Bank Marketing, vol. 24 no. 2
Type: Research Article
ISSN: 0265-2323

Keywords

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