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A new approach to clustering soil profile data using the modified distance matrix

COMPUTERS AND ELECTRONICS IN AGRICULTURE 2020年 176卷 105631-105631页

作者： Shelia, Vakhtang Hoogenboom, Gerrit Univ Florida Dept Agr & Biol Engn Gainesville FL 32611 USA Univ Florida Inst Sustainable Food Syst Gainesville FL 32611 USA

The application of different data mining methods for large soil profile datasets can be very useful for many agricultural and natural resource management applications, ranging from crop modeling to soil taxonomy. Distance or dissimilarity measures are key features of these methods. The proximity measure or the distance between vectors is calculated when they have the same dimensions. In the case of the soil profile data, the corresponding matrices representing different soils and their horizon properties usually have different dimensions. The objectives of this study were to explore a new approach for creating a semi-metric based on adjustment of the soil profile horizons, implement it in the computer application and to apply the modified distance matrix calculation to maximize the use of soil horizon properties for soil data mining. We assume that each soil horizon is homogenous while a vertical heterogeneity of soil profile is expressed through different soil horizons. Therefore, any sublayers of a horizon are characterized with the same values for its attributes as the horizon itself. In our approach, we developed matrices with the same dimension for soil profiles and calculated the proximity measure. The algorithm was implemented as an easy to use Fortran application that can calculate the modified distance matrix (MDM) for low- and high-dimensional soil profiles data. The proposed approach was shown to be effective when using existing reliable datasets, such as WISE Version 3.1, a global soil profile database developed by ISRIC. hierarchical clustering was performed using the MDM based on the original algorithm of soil profile horizons adjustment with further integration into R. The principal finding shows that a proposed modified distance matrix can be used with different clustering methods for soil profile data clustering on a horizon-by-horizon basis. This study established a new methodology for using the modified distance matrix calculation and applying it

关键词： Soil horizon Numerical classification hierarchical algorithm Ward method WISE

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Forming clusters based on strategic partnerships and circular economy for biogas production: A GIS analysis for optimal location

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BIOMASS & BIOENERGY 2021年 150卷 106097-106097页

作者： de Jesus, Romulo Henrique Gomes Barros, Murillo Vetroni Salvador, Rodrigo Souza, Jovani Taveira de Piekarski, Cassiano Moro Francisco, Antonio Carlos de Univ Tecnol Fed Parana UTFPR Postgrad Program Prod Engn PPGEP Sustainable Prod Syst Lab LESP Ponta Grossa Parana Brazil

The aim of this paper is twofold: (i) to build a model by combining an agglomerative hierarchical algorithm with multicriteria analysis and geographic information systems (GIS) in order to identify whether there are opportunities to create strategic partnerships based on geographic coordinates of raw material suppliers and the volume of raw material supply;and (ii) to apply the model in a case study in order to identify suitable locations for building a biodigester, thus establishing strategic partnerships and circular economy-based practices. The model involves four stages: (1) defining the study site, (2) building the set of cluster solutions, (3) defining the suitable locations for building a biodigester, and (4) conducting analyses of feasibility of strategic partnership and sensitivity. The model was applied in a small region and it was analyzed the possibility of creating two or three clusters. The use of the model allowed, from both quantitative and qualitative perspectives, to preliminarily identify the possibility of creating a strategic partnership, and also determine the location of a biodigester. The case study applied in southern Brazil took place in a region with high potential for generating biogas from agrowaste. A geographic map with roads, rivers, and constraints was built. Strategic partnerships, sensitivity analysis, and circular economy-based practices were discussed. The results of this work could provide useful information when using the model for other regions, and the model could easily incorporate further criteria and conditions, making it flexible and tailored to users' needs.

关键词： GIS Circular economy Biomass waste Bioenergy Strategic partnership hierarchical algorithm

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hierarchical median narrow band for level set segmentation of cervical cell nuclei

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MEASUREMENT 2021年 176卷 109232-109232页

作者： Braga, Alan M. Marques, Regis C. P. Medeiros, Fatima N. S. Neto, Jeova F. S. Rocha Bianchi, Andrea G. C. Carneiro, Claudia M. Ushizima, Daniela M. Fed Inst Ceara Fortaleza Ceara Brazil Univ Fed Ceara Fortaleza Ceara Brazil Brown Univ Providence RI 02912 USA Univ Fed Ouro Preto Ouro Preto MG Brazil Univ Calif Berkeley Berkeley Inst Data Sci Berkeley CA USA Lawrence Berkeley Natl Lab Berkeley CA USA

This paper presents a novel hierarchical nuclei segmentation algorithm for isolated and overlapping cervical cells based on a narrow band level set implementation. Our method applies a new multiscale analysis algorithm to estimate the number of clusters in each image region containing cells, which turns into the input to a narrow band level set algorithm. We assess the nuclei segmentation results on three public cervical cell image databases. Overall, our segmentation method outperformed six state-of-the-art methods concerning the number of correctly segmented nuclei and the Dice coefficient reached values equal to or higher than 0.90. We also carried out classification experiments using features extracted from our segmentation results and the proposed pipeline achieved the highest average accuracy values equal to 0.89 and 0.77 for two-class and three-class problems, respectively. These results demonstrated the suitability of the proposed segmentation algorithm to integrate decision support systems for cervical cell screening.

关键词： Cervical cell Cluster estimation hierarchical algorithm Narrow band level set Nuclei segmentation

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Systematic selection of field response measurements for excavation back analysis

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ADVANCED ENGINEERING INFORMATICS 2021年 48卷 101296-101296页

作者： Wang, Ze Zhou Bertola, Numa Joy Goh, Siang Huat Smith, Ian F. C. Natl Univ Singapore Dept Civil & Environm Engn Block E1A07-031 Engn Dr 2 Singapore 117576 Singapore Singapore ETH Ctr Future Cities Lab 1 CREATE WayCREATE Tower06-01 Singapore 138602 Singapore Swiss Fed Inst Technol EPFL Sch Architecture Civil & Environm Engn ENAC Appl Comp & Mech Lab IMAC Lausanne Switzerland

In a geotechnical excavation, back analyses are routinely performed using the measured field responses to derive the material parameter values for the different soil layers present at the site. For the purpose of back analyses, the engineers will usually make use of a portion of the large volumes of field data collected, in order to keep the computational effort to a manageable level. However, excavation back analyses using different selected sets of field response measurements may not yield the same knowledge of material parameter values. Therefore, measurements need to be carefully selected to obtain the best estimates of material parameter values. Currently, the selection of measurements is largely based on engineering heuristics;no method has been proposed to systematically quantify the expected knowledge of the parameter values that field response measurements could provide. In this paper, a hierarchical algorithm based on a joint-entropy objective function is proposed to systematically evaluate the knowledge gained from wall deflections measured by eight inclinometers at an excavation site. The algorithm ranks the inclinometers based on the expected knowledge yield of the parameter values. Back analysis using actual field response measurements is then carried out to corroborate the ranking. The rankings obtained from the back analysis results and the predictions of the hierarchical algorithm are very similar, which suggests that the latter method can aid in the judicious selection of field response measurements in order to obtain useful knowledge of material parameter values. Since the application of the hierarchical algorithm does not entail the use of actual measurements, such predictions can be made at the early stages of a project, even before the commencement of site activities.

关键词： Information entropy Joint entropy hierarchical algorithm Back analysis Finite-element analysis Geotechnical excavation

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A two-phase strategy for nonconvex clusters integrating a spectral clustering with a merging technique

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EXPERT SYSTEMS WITH APPLICATIONS 2023年 214卷

作者： Favati, Paola Menchi, Ornella CNR Inst Informat & Telemat Via G Moruzzi 1 I-56124 Pisa Italy Univ Pisa Dept Informat Largo Pontecorvo 3 I-56127 Pisa Italy

In this paper we address the problem of arbitrarily shaped clustering of points belonging to a linear space. Among the several approaches to clustering proposed in literature, the spectral clustering has become more and more popular for the case of arbitrarily shaped clusters. It depends on parameters whose choice can be critical. In order to reduce these criticalities, in this paper we propose a two-phase strategy that integrates the partitioning obtained by the spectral clustering with a merging technique which makes use only of the information already produced in the first phase by the spectral clustering. The main novelty of this approach is precisely the fact that no geometric tool is exploited in the merging phase. A numerical experimentation on artificial and real-world datasets has been performed to compare the proposed method with the spectral clustering and with two other widely used algorithms for non-convex problems, namely DBSCAN and Chameleon 2.

关键词： Similarity matrix Multiclass spectral clustering hierarchical algorithm

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Multi-Objective Optimal Charging Control of Plug-In Hybrid Electric Vehicles in Power Distribution Systems

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ENERGIES 2019年第13期12卷 2563页

作者： Li, Wei Lin, Zhiyun Cai, Kai Zhou, Hanyun Yan, Gangfeng Zhejiang Univ Coll Elect Engn Hangzhou 310027 Zhejiang Peoples R China Hangzhou Dianzi Univ Sch Automat Hangzhou 310018 Zhejiang Peoples R China Osaka City Univ Dept Elect & Informat Engn Osaka 5588585 Japan Zhejiang Univ Inst Marine Informat Sci & Technol Zhoushan 316022 Peoples R China

With the increasing popularity of plug-in hybrid electric vehicles (PHEVs), the coordinated charging of PHEVs has become an important issue in power distribution systems. This paper employs a multi-objective optimization model for coordinated charging of PHEVs in the system, in which the problem of valley filling and total cost minimization are both investigated under the system's technical constraints. To this end, a hierarchical optimal algorithm combining the water-filling-based algorithm with the consensus-based method is proposed to solve the constrained optimization problem. Moreover, a moving horizon approach is adopted to deal with the case where PHEVs arrive and leave randomly. We show that the proposed algorithm not only enhances the stability of the power load but also achieves the global minimization of vehicle owners charging costs, and its implementation is convenient in the multi-level power distribution system integrating the physical power grid with a heterogeneous information network. Numerical simulations are presented to show the desirable performance of the proposed algorithm.

关键词： coordinated charging hierarchical algorithm multi-objective optimization moving horizon approach PHEVs

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hierarchical multi-agent predictive maintenance scheduling for trains using price-based approach

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 159卷 107475-107475页

作者： Rokhforoz, Pegah Fink, Olga Swiss Fed Inst Technol Chair Intelligent Maintenance Syst Zurich Switzerland Univ Tehran Sch Elect & Comp Engn Tehran Iran

While the progress of predictive maintenance has been rising in various application fields and several feasibility studies and prototypes have been developed, the operational implementation of predictive maintenance requires a more flexible and adaptive scheduling of the predicted maintenance interventions. Contrary to the traditional preventive maintenance tasks that are typically known long in advance, predictive maintenance may require very short-term schedule changes which are also affecting the operation. Railway rolling stock has some special requirements in terms of time table adherence and vehicle scheduling and routing that make the operational implementation of predictive maintenance particularly challenging. In this paper, we propose a hierarchical multi-agent framework for the predictive maintenance scheduling of passenger railway wagons. Besides fulfilling the requirement of scheduling the maintenance of a wagon before it fails (and potentially causes delays), also the passenger demand must be satisfied and the trains must be accordingly assigned to different routes following the time table. We propose a hierarchical distributed learning algorithm using dual decomposition and mechanism design approach. The proposed framework enables to preserve local preferences and particularities and to avoid high computational cost. In the proposed method, first, we decompose the centralized problem using the dual decomposition method, and handle the passenger demand fulfillment constraints by Lagrange multiplier ("shadow price"). Furthermore, the wagons with the private information on the system health need to perform the maintenance before their failure time (with a predicted remaining useful lifetime (RUL) and the corresponding uncertainty). To achieve this aim, we propose a mechanism design approach to align the wagons' objective function to the aim of the central system using an incentive signal. The incentive signal creates a noncooperative game among the wagon

关键词： Railway wagon maintenance scheduling Train scheduling Multi-agent system hierarchical algorithm

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The Multiobjective hierarchical Planning of a Regional Water Environment-economy System

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IFAC Proceedings Volumes 1989年第10期22卷 531-536页

作者： Da Qing-Li He Jian-Min Xu Nan-Rong School of Management Southeast University Nanjing PRC

In this paper a multisubregional nonlinear dynamical waterenvironment-economy input-output model is developed which is based on the balance between production and use of outputs and the two-level scheme for treatment of water pollution. The model is combined with the water quality model of a river system in the regional area and a multisubregional waterenvironment-economy planning problem is established. In order to solve the large scale problem, a multiobjective hierarchical optimization algorithm is proposed. Theoretical analysis and computer simulation show that more factors are considered in the models and the calculations for optimization of planning are improved effectively by means of a hierarchical structure. So the method in the paper provides a useful tool for a regional waterenvironment-economy planning.

关键词： Large-scale systems input-output analysis water pollution control multiobjective optimization hierarchical algorithm

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An O(N) algorithm for computing expectation of N-dimensional truncated multi-variate normal distribution I: fundamentals

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ADVANCES IN COMPUTATIONAL MATHEMATICS 2021年第5期47卷 65-65页

作者： Huang, Jingfang Cao, Jian Fang, Fuhui Genton, Marc G. Keyes, David E. Turkiyya, George Univ N Carolina Chapel Hill NC 27515 USA King Abdullah Univ Sci & Technol Thuwal Saudi Arabia Amer Univ Beirut Beirut Lebanon

In this paper, we present the fundamentals of a hierarchical algorithm for computing the N-dimensional integral phi(a, b;A) = integral(b)(a) H(x) f (x vertical bar A)dx representing the expectation of a function H(X) where f (x vertical bar A) is the truncated multi-variate normal (TMVN) distribution with zero mean, x is the vector of integration variables for the N-dimensional random vector X, A is the inverse of the covariance matrix Sigma, and a and b are constant vectors. The algorithm assumes that H(x) is "low-rank" and is designed for properly clustered X so that the matrix A has "low-rank" blocks and "low-dimensional" features. We demonstrate the divide-and-conquer idea when A is a symmetric positive definite tridiagonal matrix and present the necessary building blocks and rigorous potential theory-based algorithm analysis when A is given by the exponential covariance model. The algorithm overall complexity is O(N) for N-dimensional problems, with a prefactor determined by the rank of the off-diagonal matrix blocks and number of effective variables. Very high accuracy results for N as large as 2048 are obtained on a desktop computer with 16G memory using the fast Fourier transform (FFT) and non-uniform FFT to validate the analysis. The current paper focuses on the ideas using the simple yet representative examples where the off-diagonal matrix blocks are rank 1 and the number of effective variables is bounded by 2, to allow concise notations and easier explanation. In a subsequent paper, we discuss the generalization of current scheme using the sparse grid technique for higher rank problems and demonstrate how all the moments of k(th) order or less (a total of O(N-k) integrals) can be computed using O(N-k) operations for k >= 2 and O(N log N) operations for k = 1.

关键词： Exponential covariance model Fourier transform hierarchical algorithm Low-dimensional structure Low-rank structure Truncated multi-variate normal distribution

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Modelling a distributed fusion system for intelligent alarm analysis

Journal of the Institution of Engineers (India), Part CP: Co...

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Journal of the Institution of Engineers (India), Part CP: Computer Engineering Division 2002年第NOV.期82卷 46-49页

作者： Shalinie, S.M. Dept. of Computer Science and Eng. Thiagarajar College of Engineering Madurai 625 015 Tamil Nadu India

Multisensor data fusion is necessary to integrate data from different sensors and extract the relevant information on the targets. While a centralized processing approach is theoretically optimal, there are significant advantages in distributing the fusion operations over multiple processing nodes. This paper discusses architectures for distributed fusion, whereby each node processes the data from its own set of sensors and communicates with other nodes to improve on the estimates. Information flow in distributed fusion systems is modelled using information graph. The approach is verified for intelligent alarm analysis process.

关键词： Alarm analysis Distributed approach Fuzzy logic hierarchical algorithm Multisensor

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