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Multi-criteria prioritization of the renewable power plants in Australia using the fuzzy logic in decision-making method(FMCDM)

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Clean Energy 2022年第1期6卷 16-34页

作者： Amin Aryanfar Aslan Gholami Payam Ghorbannezhad Bijan Yeganeh Mahdi Pourgholi Majid Zandi Svetlana Stevanovic Faculty of Mechanical and Energy Engineering Shahid Beheshti UniversityTehranIran Faculty of New Technologies and Energy Engineering Shahid Beheshti UniversityTehranIran Faculty of Civil Water&Environmental EngineeringShahid Beheshti UniversityTehranIran Centre for Air Pollution Energy and Health ResearchGlebeNew South Wales 2037Australia Faculty of Electrical Engineering Shahid Beheshti UniversityTehranIran Faculty of Science Engineering&Built EnvironmentSchool of EngineeringDeakin UniversityGeelongVictoria 3220Australia

The presented study focused on developing an innovative decision-making framework to select the best renewable-power-plant technologies,considering comprehensive techno-economic and environmental variables.Due to the favourable conditions,Australia was selected as the case study.A fuzzy-logic method and analytical hierarchy process were applied to prioritize different renewable-energy power plants.The techno-economic factors included levelized cost of energy,initial cost,simple payback time,and operation and maintenance costs along with environmental factors including carbon payback time,energy payback time and greenhouse-gas emissions were used to rank the power plants.The results showed that the capital cost and simple payback time had the highest priority from an economic point of view.In comparison,greenhouse-gas emissions and carbon payback time were the dominant environmental factors.The analysis results provided economic and environmental priority tables for developing different power plants in the current state and a future scenario by 2030.The fuzzy results and pairwise composite matrix of alternatives indicated that the onshore wind,offshore wind,single-axis tracker polycrystalline photovoltaic,single-axis tracker monocrystalline photovoltaic,fix-tilted polycrystalline photovoltaic and fix-tilted monocrystalline photovoltaic scored the highest in the current state.In contrast,by 2030,the single-axis tracker photovoltaic power plants will be the best choice in the future scenario in Australia.Finally,the results were used and analysed to recommend and suggest several policy implementations and future research studies.

关键词： photovoltaic wind fuzzy logic analytical hierarchy process prioritization

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Bug prioritization Using Average One Dependence Estimator

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Intelligent Automation & Soft Computing 2023年第6期36卷 3517-3533页

作者： Kashif Saleem Rashid Naseem Khalil Khan Siraj Muhammad Ikram Syed Jaehyuk Choi Department of IT and Computer Science Institute of Applied Sciences and TechnologyPakAustriaFochhshuleHaripurPakistan Faculty of Computer Sciences and Information Technology Superior UniversityLahore54660Pakistan Department of Computer Science Shaheed Benazir Bhutto UniversitySheringalUpper DirKhyber PakhtunkhwaPakitan School of Computing Gachon University1342Seongnam-daeroSujeong-guSeongnam-si13120Korea

Automation software need to be continuously updated by addressing software bugs contained in their repositories.However,bugs have different levels of importance;hence,it is essential to prioritize bug reports based on their sever-ity and importance.Manually managing the deluge of incoming bug reports faces time and resource constraints from the development team and delays the resolu-tion of critical bugs.Therefore,bug report prioritization is vital.This study pro-poses a new model for bug prioritization based on average one dependence estimator;it prioritizes bug reports based on severity,which is determined by the number of attributes.The more the number of attributes,the more the severity.The proposed model is evaluated using precision,recall,F1-Score,accuracy,G-Measure,and Matthew’s correlation coefficient.Results of the proposed model are compared with those of the support vector machine(SVM)and Naive Bayes(NB)models.Eclipse and Mozilla datasetswere used as the sources of bug reports.The proposed model improved the bug repository management and out-performed the SVM and NB models.Additionally,the proposed model used a weaker attribute independence supposition than the former models,thereby improving prediction accuracy with minimal computational cost.

关键词： Bug report triaging prioritization support vector machine Naive Bayes

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prioritization of Sub-Watersheds in Ruparel Watershed, Rajasthan Based on Morphometric and Land Use/Land Cover Analysis Using Remote Sensing and GIS

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International Journal of Geosciences 2022年第2期13卷 138-154页

作者： Munahzah Meraj Akram Javed Department of Geology Aligarh Muslim University Aligarh India

Watershed prioritization is considered as the most significant aspect in watershed resource management and development program. The present work attempts to prioritize seventeen sub-watersheds in Ruparel watershed of Alwar district of Rajasthan, India. For prioritization of sub-watersheds, morphometric and land use/land cover (LULC) analysis were performed using remote sensing and GIS. Base map of the study area has been derived from SOI toposheet on 1:50,000 scale whereas LULC mapping was done using IRS P6 LISS III data. Standard methods for drainage morphometry have been followed for computing morphometric parameters such as linear and shape for seventeen sub-watersheds and allotted ranks based on their relationship with erodibility and a compound value has been calculated for final ranking. Five main LULC categories were computed and were assigned priority ranks and subsequently a compound parameter was determined for final ranking. Integration of both morphometric and LULC results reveal that SBW5, SBW7, SBW12 and SBW16 are the common sub-watersheds that fall under high priority, SBW3 falls under Medium category and SBW11 comes under low priority. The results of the analysis can be used to identify the sub-watersheds which need immediate restoration and will eventually help in watershed resource management for sustainable development.

关键词： prioritization Watershed Resource Management Morphometry Land Use/Land Cover Analysis

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VPOT:A Customizable Variant prioritization Ordering Tool for Annotated Variants

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Genomics, Proteomics & Bioinformatics 2019年第5期17卷 540-545页

作者： Eddie Ip Gavin Chapman David Winlaw Sally LDunwoodie Eleni Giannoulatou Victor Chang Cardiac Research Institute Sydney 2010Australia St Vincent’s Clinical School University of New South WalesSydney 2052Australia Heart Centre for Children The Children’s Hospital at WestmeadSydney 2145Australia Sydney Medical School University of SydneySydney 2050Australia School of Biotechnology and Biomolecular Sciences University of New South WalesSydney 2033Australia

Next-generation sequencing(NGS) technologies generate thousands to millions of genetic variants per sample.Identification of potential disease-causal variants is labor intensive as it relies on filtering using various annotation metrics and consideration of multiple pathogenicity prediction scores.We have developed VPOT(variant prioritization ordering tool),a python-based command line tool that allows researchers to create a single fully customizable pathogenicity ranking score from any number of annotation values,each with a user-defined weighting.The use of VPOT can be informative when analyzing entire cohorts,as variants in a cohort can be prioritized.VPOT also provides additional functions to allow variant filtering based on a candidate gene list or by affected status in a family pedigree.VPOT outperforms similar tools in terms of efficacy,flexibility,scalability,and computational performance.VPOT is freely available for public use at Git Hub(https://***/VCCRI/VPOT/).Documentation for installation along with a user tutorial,a default parameter file,and test data are provided.

关键词： Next-generation sequencing Pathogenicity predictions Variant prioritization Customizable ranking Genomic annotation

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The Strategy of Third-Party Mediation Based on the Option prioritization in the Graph Model

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Journal of Systems Science and Systems Engineering 2019年第4期28卷 399-414页

作者： Zhenggao Wu Haiyan Xu Ginger Y. Ke College of Economics and Management Nanjing University of Aeronautics and Astronautics Nanjing 211106 China Faculty of Business Administration Memorial University of Newfoundland St. John's Newfoundland and Labrador A1B 3X5 Canada

The resolution of real-world conflicts is often supported by third-party intervention (i.e., media? tion). This paper proposes a possible mediation support in the form of a reverse optimization procedure under the framework of the Graph Model for Conflict Resolution (GMCR). The approach computes minimal priority adjustments of preference statements that are necessary to achieve a desired agreement. A mathematical model, based on the matrix form of GMCR, is developed to analyze this third-party mediation problem. Thereby;this study makes a first attempt to obtain option-based mediation strategies, which add comprehensiveness to the traditional state-based strategies, yet are easier to understand and hence more acceptable to the conflict participants. To illustrate the practicality;the proposed procedure is applied to a medical dispute between a patient and a hospital, with the aim to suggest changes in the ordering of preference statements that lead to a desired outcome.

关键词： Graph Model for Conflict Resolution third party mediation option prioritization minimal adjustment

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Express analysis for prioritization:Best-Worst Scaling alteration to System 1

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Journal of Management Analytics 2020年第1期7卷 12-27页

作者： Stan Lipovetsky Minneapolis MinnesotaUSA

The work considers modification of the Best–Worst Scaling(BWS)to the so-called System 1(S1)approach.S1 was described by D.Kahneman as a spontaneous and automatic reaction by an unconsciousway in which human decision-makers choose among multiple alternatives.Application of S1 can be seen as a simplified BWS for data eliciting and express analysis of prioritization between many compared items.In S1,a respondent picks the items with which she feels“happy”,and those can be one,several,all,or none items in a task.Estimation of utilities is performed by multinomial-logit modeling with different optimization criteria which produce parameters of the models and choice probabilities of the items.Numerical examples by marketing research data are encouraging and demonstrating that spontaneous choice decisions can make S1 approach very fast,efficient,and convenient for express analysis of items prioritization,especially for big data.

关键词： System 1 BWS max diff MNLutility choice probability prioritization

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SWPT:An automated GIS-based tool for prioritization of sub-watersheds based on morphometric and topo-hydrological factors

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Geoscience Frontiers 2019年第6期10卷 2167-2175页

作者： Omid Rahmati Mahmood Samadi Himan Shahabi Ali Azareh Elham Rafiei-Sardooi Hossein Alilou Assefa M.Melesse Biswajeet Pradhan Kamran Chapi Ataollah Shirzadi Geographic Information Science Research Group Ton Duc Thang UniversityHo Chi Minh CityViet Nam Faculty of Environment and Labour Safety Ton Duc Thang UniversityHo Chi Minh CityViet Nam Faculty of Natural Resources University of TehranKarajIran Department of Geomorphology Faculty of Natural ResourcesUniversity of KurdistanSanandajIran Department of Geography University of JiroftKermanIran Faculty of Natural Resources University of JiroftKermanIran Aquatic Ecodynamics UWA School of Agriculture and EnvironmentThe University of Western AustraliaCrawleyWA6009Australia Department of Earth and Environment AHC 5-390Florida International UniversityUSA Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS) Faculty of Engineering and ITUniversity of Technology SydneyNSW2007Australia Department of Energy and Mineral Resources Engineering Choongmu-gwanSejong University209 Neungdong-roGwangjin-guSeoul05006Republic of Korea Department of Rangeland and Watershed Management Faculty of Natural ResourcesUniversity of KurdistanSanandajIran

The sub-watershed prioritization is the ranking of different areas of a river basin according to their need to proper planning and management of soil and water resources.Decision makers should optimally allocate the investments to critical sub-watersheds in an economically effective and technically efficient manner.Hence,this study aimed at developing a user-friendly geographic information system(GIS)tool,Sub-Watershed prioritization Tool(SWPT),using the Python programming language to decrease any possible uncertainty.It used geospatial-statistical techniques for analyzing morphometric and topohydrological factors and automatically identifying critical and priority sub-watersheds.In order to assess the capability and reliability of the SWPT tool,it was successfully applied in a watershed in the Golestan Province,Northern Iran.Historical records of flood and landslide events indicated that the SWPT correctly recognized critical sub-watersheds.It provided a cost-effective approach for prioritization of sub-watersheds.Therefore,the SWPT is practically applicable and replicable to other regions where gauge data is not available for each sub-watershed.

关键词： SWPT Watershed prioritization GIS Effective management

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Multi-objective test case prioritization based on multi-population cooperative particle swarm optimization

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The Journal of China Universities of Posts and Telecommunications 2020年第1期27卷 38-50页

作者： Wang Hongman Li Jinzhong Xing Ying Zhou Xiaoguang Institute of Network Technology Beijing University of Posts and TelecommunicationsBeijing 100876China School of Automation Beijing University of Posts and TelecommunicationsBeijing 100876China Information Networks Engineering Research Center Ministry of EducationBeijing 100876China

Test case prioritization(TCP) technique is an efficient approach to improve regression testing activities. With the continuous improvement of industrial testing requirements, traditional single-objective TCP is limited greatly, and multi-objective test case prioritization(MOTCP) technique becomes one of the hot topics in the field of software testing in recent years. Considering the problems of traditional genetic algorithm(GA) and swarm intelligence algorithm in solving MOTCP problems, such as falling into local optimum quickly and weak stability of the algorithm, a MOTCP algorithm based on multi-population cooperative particle swarm optimization(MPPSO) was proposed in this paper. Empirical studies were conducted to study the influence of iteration times on the proposed MOTCP algorithm, and compare the performances of MOTCP based on single-population particle swarm optimization(PSO) and MOTCP based on non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) with the MOTCP algorithm proposed in this paper. The results of experiments show that the TCP algorithm based on MPPSO has stronger global optimization ability, is not easy to fall into local optimum, and can solve the MOTCP problem better than TCP algorithm based on the single-population PSO and NSGA-Ⅱ.

关键词： regression testing test case prioritization multi-population cooperative particle swarm optimization multi-objective optimization

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Comparative study of network-based prioritization of protein domains associated with human complex diseases

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Frontiers of Electrical and Electronic Engineering in China 2010年第2期5卷 107-118页

作者： Wangshu ZHANG Yong CHEN Rui JIANG MOE Key Laboratory of Bioinformatics and Bioinformatics Division TNLIST/Department of AutomationTsinghua UniversityBeijing 100084China School of Sciences University of JinanJinan 250014China

Domains are basic structural and functional unit of proteins,and,thus,exploring associations between protein domains and human inherited diseases will greatly improve our understanding of the pathogenesis of human complex diseases and further benefit the medical prevention,diagnosis and treatment of these diseases.Based on the assumption that deleterious nonsynonymous single nucleotide polymorphisms(nsSNPs)underlying human complex diseases may actually change structures of protein domains,affect functions of corresponding proteins,and finally result in these diseases,we compile a dataset that contains 1174 associations between 433 protein domains and 848 human disease phenotypes.With this dataset,we compare two approaches(guilt-by-association and correlation coefficient)that use a domain-domain interaction network and a phenotype similarity network to prioritize associations between candidate domains and human disease phenotypes.We implement these methods with three distance measures(direct neighbor,shortest path with Gaussian kernel,and diffusion kernel),demonstrate the effectiveness of these methods using three large-scale leave-one-out cross-validation experiments(random control,simulated linkage interval,and whole-genome scan),and evaluate the performance of these methods in terms of three criteria(mean rank ratio,precision,and AUC score).Results show that both methods can effectively prioritize domains that are associated with human diseases at the top of the candidate list,while the correlation coefficient approach can achieve slightly higher performance in most cases.Finally,taking the advantage that the correlation coefficient method does not require known disease-domain associations,we calculate a genome-wide landscape of associations between 4036 protein domains and 5080 human disease phenotypes using this method and offer a freely accessible web interface for this landscape.

关键词： protein domains disease phenotypes prioritization guilt-by-association correlation coefficient

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prioritization of Promising Wadi Wala Watershed (Southern Jordan) Using GIS-Based Morphometric Analysis and Multivariate Statistics

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Open Journal of Geology 2018年第2期8卷 135-160页

作者： Yahya Farhan Ali Anbar Dalal Zreqat Haifa Almohammad Sireen Alshawamreh Amman Jordan Department of Geography University of Jordan Amman Jordan FAO Sustainability Land Management Member Amman Jordan

GIS-based morphometric analysis was employed for prioritization of the Wadi Wala catchment, southern Jordan. Twenty three fourth-order sub-basins were prioritized based on morphometric analysis, then appropriate soil and water conservation measures were proposed. Digital Elevation Model (DEM) and Arc GIS were used to delineate watersheds and to extract the drainage networks, and other required thematic maps (elevation and slope). LANDSAT data was used to prepare land use/land cover map, and a soil map was digitized using Arc GIS software. Linear and shape parameters were computed to prioritize 23 sub-watersheds, and ranks were designated based on the calculated compound parameter (Cp). Sub-basins grouped under a high priority class are exposed to high erosion risk;thus, they are of high potential for applying soil and water conservation measures. The current study substantiates the capability of morphometric analysis method, and geospatial technology in watershed prioritization. The Discriminant Analysis (DA) employed validates the priority classes (high, moderate, and low priority) achieved based on morphometric analysis, where they found statistically distinct from each other. Thus, it can be concluded that prioritization based only on morphometric analysis method is consistent, reliable, and of high capacity using GIS platform. Priority map along with soil, land user/cover, and slope information will help decision makers to execute proper soil and water conservation programs in the rainfed highlands of Jordan.

关键词： Morphometric Analysis prioritization Soil Erosion Loss Discriminant Analysis GIS Jordan

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