Multi-objective optimal evolutionary algorithms (MOEAs) are a kind of new effective algorithms to solve Multi-objective optimal problem (MOP). Because ranking, a method which is used by most MOEAs to solve MOP, has so...Multi-objective optimal evolutionary algorithms (MOEAs) are a kind of new effective algorithms to solve Multi-objective optimal problem (MOP). Because ranking, a method which is used by most MOEAs to solve MOP, has some shortcoming s, in this paper, we proposed a new method using tree structure to express the relationship of solutions. Experiments prove that the method can reach the Pare-to front, retain the diversity of the population, and use less time.展开更多
为掌握服役时期的海上风机基础状态并对海上风机基础状态进行评估,提出一套结合故障树分析(Fault Tree Analysis,FTA)法、层次分析(Analytic Hierarchy Process,AHP)法和模糊综合评价法的海上风机基础状态评价模型。针对导管架式海上风...为掌握服役时期的海上风机基础状态并对海上风机基础状态进行评估,提出一套结合故障树分析(Fault Tree Analysis,FTA)法、层次分析(Analytic Hierarchy Process,AHP)法和模糊综合评价法的海上风机基础状态评价模型。针对导管架式海上风机基础,考虑海洋腐蚀和海底冲刷,通过p-y曲线法模拟桩-土相互作用,在风浪流载荷的作用下进行动力响应分析,采用故障树对其失效模式进行分析,确定评价指标,构造判断矩阵计算指标权重,运用模糊综合评价法对各指标和整体进行评价。该模型结合各评价方法的优点,使评价结果更有说服力,可为海上风电场运行维护管理提供技术参考。展开更多
In applications such as image retrieval and recognition, precise edge detection for interested regions plays a decisive role. Existing methods generally take little care about local characteristics, or become time con...In applications such as image retrieval and recognition, precise edge detection for interested regions plays a decisive role. Existing methods generally take little care about local characteristics, or become time consuming if every detail is considered. In the paper, a new method is put forward based on the combination of effective image representation and multiscale wavelet analysis. A new object tree image representation is introduced. Then a series of object trees are constructed based on wavelet transform modulus maxima at different scales in descending order. Computation is only needed for interested regions. Implementation steps are also given with an illustrative example.展开更多
This paper builds multi-objective effect evaluation indicator system of smart grid construction from five connotations including strong and reliable, clean and green, friendly and interactive, transparent and open, ec...This paper builds multi-objective effect evaluation indicator system of smart grid construction from five connotations including strong and reliable, clean and green, friendly and interactive, transparent and open, economical and effective, which is embodied in the power generation, transmission, transformation, distribution, consumption, dispatching and information communication platform of smart grid. Taking the construction of smart grid in a certain area of China as an example, this paper uses analytic hierarchy process (AHP) to make an empirical analysis on it, and makes a comprehensive and objective evaluation on its construction effect.展开更多
Unlike the case in Mediterranean countries, where olive oil consumption is driven by habit or tradition, in a population where olive oil consumption rates are considerably low, it appears reasonable to suppose that th...Unlike the case in Mediterranean countries, where olive oil consumption is driven by habit or tradition, in a population where olive oil consumption rates are considerably low, it appears reasonable to suppose that the initial decision to buy a fairly expensive product—as is the case with olive oil in the Uruguayan market—may result from an individual’s overall interest in health-related issues and/or their acquaintance with relevant nutritional properties of the particular product—in this case, olive oil. Consumer subjective and objective knowledge, interest in health-related issues, and demographic variables were studied for their potential relationship (explanatory capacity) with olive oil consumption frequency, using a sample of 256 inhabitants of Montevideo (Uruguay). Several of the studied variables were found to relate to olive oil consumption, such as subjective and objective knowledge, age, education level, marital status, and interest in health-related issues. Subjective knowledge was found to have the highest explanatory capacity. An increase in subjective knowledge is therefore expected to lead to an increase in consumption frequency among regular olive oil consumers, while it may also encourage less frequent or non-consumers to purchase olive oil and become acquainted with the product.展开更多
As forest is of great significance for our whole development and the sustainable plan is so focus on it. It is very urgent for us to have the whole distribution,stock volume and other related information about that. S...As forest is of great significance for our whole development and the sustainable plan is so focus on it. It is very urgent for us to have the whole distribution,stock volume and other related information about that. So the forest inventory program is on our schedule. Aiming at dealing with the problem in extraction of dominant tree species,we tested the highly hot method-object-based analysis. Based on the ALOS image data,we combined multi-resolution in e Cognition software and fuzzy classification algorithm. Through analyzing the segmentation results,we basically extract the spruce,the pine,the birch and the oak of the study area. Both the spectral and spatial characteristics were derived from those objects,and with the help of GLCM,we got the differences of each species. We use confusion matrix to do the Classification accuracy assessment compared with the actual ground data and this method showed a comparatively good precision as 87% with the kappa coefficient 0. 837.展开更多
Land suitability analysis of Moringa oleifera tree cultivation is important to enhance its product,as the demand forthis tree for medicinal values and food sources is increasing worldwide.Therefore,this study aimed to...Land suitability analysis of Moringa oleifera tree cultivation is important to enhance its product,as the demand forthis tree for medicinal values and food sources is increasing worldwide.Therefore,this study aimed to assess suitableland for Moringa oleifera tree cultivation by using the integration of multi-criteria evaluation with geospatialtechnologies in the Dhidhessa catchment,western Ethiopia.Five parameters,namely:slope,land use and landcover(LULC),soil texture,land surface temperature,and rainfall data,were used in this study.The land suitabilityevaluation of Moringa oleifera is classified into three classes as highly suitable,moderately suitable,and notsuitable.The results revealed that,about 344.4 km2(12.2%)of the area is categorized into highly suitable,and2343.7 km2(83%)is moderately suitable for Moringa tree,whereas,137.2 km2(4.9%)is categorized as notsuitable for Moringa oleifera tree cultivation.Hence,based on the finding of the study,we suggested that farmers andother stakeholders can cultivate Moringa oleifera trees in the Dhidhessa catchment.展开更多
为了快速检测和统计杨梅树的数量,该研究提出了一种基于改进YOLOv7的杨梅树单木检测模型:YOLOv7-ACGDmix。首先,对YOLOv7的可扩展高效长程注意力网络(extended-efficient long-range attention networks, E-ELAN)进行改进,通过融合兼具...为了快速检测和统计杨梅树的数量,该研究提出了一种基于改进YOLOv7的杨梅树单木检测模型:YOLOv7-ACGDmix。首先,对YOLOv7的可扩展高效长程注意力网络(extended-efficient long-range attention networks, E-ELAN)进行改进,通过融合兼具卷积和注意力机制优势的ACmix(a mixed model that enjoys the benefit of both self-attention and convolution)结构得到AC-E-ELAN模块,提升模型的学习和推理能力,引入可变形卷积(deformable convolutional networks version 2, DCNv2)结构得到DCNv2-E-ELAN模块,增强模型对不同尺寸目标的提取能力;其次,采用内容感知特征重组(content-aware reassembly of features, CARAFE)上采样模块,提高模型对重要特征的提取能力;然后,在主干和头部网络部分添加全局注意力机制(global-attention mechanism, GAM),强化特征中的语义信息和位置信息,提高模型特征融合能力;最后,采用WIoU(wise intersection over union)损失函数减少因正负样本数据不平衡造成的干扰,增强模型的泛化性。在公开数据集上的试验结果表明,YOLOv7-ACGDmix模型的精确率达到89.1%,召回率达到89.0%,平均精度均值(mean average precision, mAP)达到95.1%,F_(1)-score达到89.0%,相比于原YOLOv7模型分别提高1.8、4.0、2.3和3.0个百分点。与Faster R-CNN、SSD、YOLOv8模型相比,改进模型的平均精度均值(mAP_(0.5))分别提高了9.8、2.2、0.7个百分点。实地采集杨梅树样本数据的检测精确率87.3%、召回率85.7%。试验表明,改进模型为基于无人机影像的杨梅树单木检测提供了一种有效的解决方案,对果园精准管理的发展具有重要意义。展开更多
基金Supported by the National Natural Science Foundation of China(60073043,70071042,60133010)
文摘Multi-objective optimal evolutionary algorithms (MOEAs) are a kind of new effective algorithms to solve Multi-objective optimal problem (MOP). Because ranking, a method which is used by most MOEAs to solve MOP, has some shortcoming s, in this paper, we proposed a new method using tree structure to express the relationship of solutions. Experiments prove that the method can reach the Pare-to front, retain the diversity of the population, and use less time.
文摘为掌握服役时期的海上风机基础状态并对海上风机基础状态进行评估,提出一套结合故障树分析(Fault Tree Analysis,FTA)法、层次分析(Analytic Hierarchy Process,AHP)法和模糊综合评价法的海上风机基础状态评价模型。针对导管架式海上风机基础,考虑海洋腐蚀和海底冲刷,通过p-y曲线法模拟桩-土相互作用,在风浪流载荷的作用下进行动力响应分析,采用故障树对其失效模式进行分析,确定评价指标,构造判断矩阵计算指标权重,运用模糊综合评价法对各指标和整体进行评价。该模型结合各评价方法的优点,使评价结果更有说服力,可为海上风电场运行维护管理提供技术参考。
文摘In applications such as image retrieval and recognition, precise edge detection for interested regions plays a decisive role. Existing methods generally take little care about local characteristics, or become time consuming if every detail is considered. In the paper, a new method is put forward based on the combination of effective image representation and multiscale wavelet analysis. A new object tree image representation is introduced. Then a series of object trees are constructed based on wavelet transform modulus maxima at different scales in descending order. Computation is only needed for interested regions. Implementation steps are also given with an illustrative example.
文摘This paper builds multi-objective effect evaluation indicator system of smart grid construction from five connotations including strong and reliable, clean and green, friendly and interactive, transparent and open, economical and effective, which is embodied in the power generation, transmission, transformation, distribution, consumption, dispatching and information communication platform of smart grid. Taking the construction of smart grid in a certain area of China as an example, this paper uses analytic hierarchy process (AHP) to make an empirical analysis on it, and makes a comprehensive and objective evaluation on its construction effect.
文摘Unlike the case in Mediterranean countries, where olive oil consumption is driven by habit or tradition, in a population where olive oil consumption rates are considerably low, it appears reasonable to suppose that the initial decision to buy a fairly expensive product—as is the case with olive oil in the Uruguayan market—may result from an individual’s overall interest in health-related issues and/or their acquaintance with relevant nutritional properties of the particular product—in this case, olive oil. Consumer subjective and objective knowledge, interest in health-related issues, and demographic variables were studied for their potential relationship (explanatory capacity) with olive oil consumption frequency, using a sample of 256 inhabitants of Montevideo (Uruguay). Several of the studied variables were found to relate to olive oil consumption, such as subjective and objective knowledge, age, education level, marital status, and interest in health-related issues. Subjective knowledge was found to have the highest explanatory capacity. An increase in subjective knowledge is therefore expected to lead to an increase in consumption frequency among regular olive oil consumers, while it may also encourage less frequent or non-consumers to purchase olive oil and become acquainted with the product.
文摘As forest is of great significance for our whole development and the sustainable plan is so focus on it. It is very urgent for us to have the whole distribution,stock volume and other related information about that. So the forest inventory program is on our schedule. Aiming at dealing with the problem in extraction of dominant tree species,we tested the highly hot method-object-based analysis. Based on the ALOS image data,we combined multi-resolution in e Cognition software and fuzzy classification algorithm. Through analyzing the segmentation results,we basically extract the spruce,the pine,the birch and the oak of the study area. Both the spectral and spatial characteristics were derived from those objects,and with the help of GLCM,we got the differences of each species. We use confusion matrix to do the Classification accuracy assessment compared with the actual ground data and this method showed a comparatively good precision as 87% with the kappa coefficient 0. 837.
文摘Land suitability analysis of Moringa oleifera tree cultivation is important to enhance its product,as the demand forthis tree for medicinal values and food sources is increasing worldwide.Therefore,this study aimed to assess suitableland for Moringa oleifera tree cultivation by using the integration of multi-criteria evaluation with geospatialtechnologies in the Dhidhessa catchment,western Ethiopia.Five parameters,namely:slope,land use and landcover(LULC),soil texture,land surface temperature,and rainfall data,were used in this study.The land suitabilityevaluation of Moringa oleifera is classified into three classes as highly suitable,moderately suitable,and notsuitable.The results revealed that,about 344.4 km2(12.2%)of the area is categorized into highly suitable,and2343.7 km2(83%)is moderately suitable for Moringa tree,whereas,137.2 km2(4.9%)is categorized as notsuitable for Moringa oleifera tree cultivation.Hence,based on the finding of the study,we suggested that farmers andother stakeholders can cultivate Moringa oleifera trees in the Dhidhessa catchment.
文摘为了快速检测和统计杨梅树的数量,该研究提出了一种基于改进YOLOv7的杨梅树单木检测模型:YOLOv7-ACGDmix。首先,对YOLOv7的可扩展高效长程注意力网络(extended-efficient long-range attention networks, E-ELAN)进行改进,通过融合兼具卷积和注意力机制优势的ACmix(a mixed model that enjoys the benefit of both self-attention and convolution)结构得到AC-E-ELAN模块,提升模型的学习和推理能力,引入可变形卷积(deformable convolutional networks version 2, DCNv2)结构得到DCNv2-E-ELAN模块,增强模型对不同尺寸目标的提取能力;其次,采用内容感知特征重组(content-aware reassembly of features, CARAFE)上采样模块,提高模型对重要特征的提取能力;然后,在主干和头部网络部分添加全局注意力机制(global-attention mechanism, GAM),强化特征中的语义信息和位置信息,提高模型特征融合能力;最后,采用WIoU(wise intersection over union)损失函数减少因正负样本数据不平衡造成的干扰,增强模型的泛化性。在公开数据集上的试验结果表明,YOLOv7-ACGDmix模型的精确率达到89.1%,召回率达到89.0%,平均精度均值(mean average precision, mAP)达到95.1%,F_(1)-score达到89.0%,相比于原YOLOv7模型分别提高1.8、4.0、2.3和3.0个百分点。与Faster R-CNN、SSD、YOLOv8模型相比,改进模型的平均精度均值(mAP_(0.5))分别提高了9.8、2.2、0.7个百分点。实地采集杨梅树样本数据的检测精确率87.3%、召回率85.7%。试验表明,改进模型为基于无人机影像的杨梅树单木检测提供了一种有效的解决方案,对果园精准管理的发展具有重要意义。
