Prediction of Blast-Induced Ground Vibration in an Open-Pit Mine by a Novel Hybrid Model Based on Clustering and Artificial Neural Network

Natural Resources Research - Ground vibration (PPV) is one of the hazard effects induced by blasting operations in open-pit mines, which can affect the surrounding structures, particularly the...     

Prediction of Flyrock in Mine Blasting: A New Computational Intelligence Approach

Natural Resources Research - Blasting is the predominant rock fragmentation technique in civil constructions, underground and surface mines. Flyrock is the unwanted throw of rock fragments during...     

A Novel Artificial Intelligence Approach to Predict Blast-Induced Ground Vibration in Open-Pit Mines Based on the Firefly Algorithm and Artificial Neural Network

Natural Resources Research - The primary purpose of this study was to develop a novel hybrid artificial intelligence model, with a robust performance, to predict ground vibration induced by bench...     

Prediction of Blast-Induced Ground Vibration Intensity in Open-Pit Mines Using Unmanned Aerial Vehicle and a Novel Intelligence System

Natural Resources Research - Predicting and reducing blast-induced ground vibrations is a common concern among engineers and mining enterprises. Dealing with these vibrations is a challenging issue...     

Predicting Blast-Induced Air Overpressure: A Robust Artificial Intelligence System Based on Artificial Neural Networks and Random Forest

Natural Resources Research - Blasting is the most popular method for rock fragmentation in open-pit mines. However, the side effects caused by blasting operations include ground vibration, air...     

Performance of Hybrid SCA-RF and HHO-RF Models for Predicting Backbreak in Open-Pit Mine Blasting Operations

Natural Resources Research - Backbreak is an adverse phenomenon in blasting operation, which can cause, among others, mine walls instability, falling down of machinery, drilling efficiency...     

Prediction of Dust Emission Due to Open Pit Mine Blasting Using a Hybrid Artificial Neural Network

Natural Resources Research - This study developed a new perspective of artificial neural networks using dimensional analysis to be applicable to certain prediction problems. To this end,...     

Evaluation and Optimization of Prediction of Toe that Arises from Mine Blasting Operation Using Various Soft Computing Techniques

Natural Resources Research - Drilling and blasting operations are one of the most effective techniques for rock removal in mines. However, these operations are associated with some environmental...     

Application of Artificial Intelligence to Estimate Oil Flow Rate in Gas-Lift Wells

Natural Resources Research - Optimization and monitoring schemes for oil well and reservoir system require accurate estimation of production rate. Real-time monitoring is conducted typically using...     

Prediction of Blast-Induced Ground Vibration in Open-Pit Mines Using a New Technique Based on Imperialist Competitive Algorithm and M5Rules

Natural Resources Research - In this paper, blast-induced ground vibration (BIGV) was considered as the primary objective, and a new artificial intelligence system was proposed to predict BIGV with...     

ORELM: A Novel Machine Learning Approach for Prediction of Flyrock in Mine Blasting

Blast-induced flyrock is a hazardous and undesirable phenomenon that may occur in surface mines, especially when blasting takes place near residential areas. Therefore, accurate prediction of flyrock distance is of high significance in the determination of the statutory danger area. To this end, there is a practical need to propose an accurate model to predict flyrock. Aiming at this topic, this study presents two machine learning models, including extreme learning machine (ELM) and outlier robust ELM (ORELM), for predicting flyrock. To the best of our knowledge, this is the first work that investigates the use of ORELM model in the field of flyrock prediction. To construct and verify the proposed ELM and ORELM models, a database including 82 datasets has been collected from the three granite quarry sites in Malaysia. Additionally, artificial neural network (ANN) and multiple regression models were used for comparison. According to the results, both ELM and ORELM models performed satisfactorily, and their performances were far better compared to the performances of ANN and multiple regression models.

     

Evaluation and Assessment of Blast-Induced Ground Vibrations in an Underground Gold Mine: A Case Study

Natural Resources Research - Ground vibrations induced during rock fragmentation by blasting remain a potential source of hazard for the stability of nearby structures. In this paper, to forecast...     

沙丘不同部位土壤呼吸对人工降水的响应

 利用LI-8100土壤呼吸测量仪,对古尔班通古特沙漠南缘阜康北部地区沙丘不同部位（坡底、坡中、坡顶）的土壤呼吸速率进行了测量,探讨了沙丘不同部位土壤呼吸速率对降雨的响应,分析了土壤水分和土壤温度对土壤呼吸速率的影响。结果表明:①沙丘不同部位土壤呼吸速率的日变化呈“双峰曲线”,而增雨处理后,土壤呼吸速率的日变化曲线大部分转变为“单峰曲线”。②增雨处理增加了沙丘不同部位土壤呼吸速率的变化幅度、平均值和极差,推后了土壤呼吸速率最大值到来的时间。③土壤呼吸速率与土壤温度的相关性对降雨表现出积极的响应,降雨改变了土壤温度的日变化曲线类型,提高了土壤温度与土壤呼吸速率的相关系数。④非增雨处理时,沙丘坡底、坡中和坡顶的土壤呼吸速率与土壤水分的相关性系数均较高,而增雨处理后,土壤呼吸速率与土壤水分的相关系数有所下降,仅坡中的相关系数通过了α=0.01的显著性检验。     

Deep Learning for Prediction of Water Quality Index Classification: Tropical Catchment Environmental Assessment

Natural Resources Research - River water quality modeling using crucial artificial intelligent (AI) models has become an essential tool for river assessment and management. The simplified approach...     

西安南郊不同人工植被下土壤CO2浓度研究

 利用红外CO2监测仪对西安南郊不同植被、不同深度条件下的土壤CO2浓度进行了多次昼夜观测。观测结果表明:从早8:00到次日早8:00,土壤CO2浓度具有从低到高再到低的昼夜变化规律,这种变化特点与昼夜温度变化基本一致,但两者在时间上并不完全同步；土壤CO2浓度从总体来看是白天和夜间很接近；松树林下的土壤CO2浓度大于草地土壤CO2浓度,草地土壤CO2浓度大于竹林下的土壤CO2浓度。     

兰州市城市热岛效应评价与灰色预测

利用兰州市及其郊区（永登、榆中、皋兰3县）1958—2004年气象观测资料分析了兰州市热岛强度的年变化规律,结果表明,1975年以后,兰州市城市热岛效应呈上升趋势,但热岛强度整体保持在3.0 ℃以下;1981—1998年平均热岛强度为3.30 ℃,1990年以后城郊热岛强度增加到3.6 ℃以上;1996年达到最高为4.25 ℃;根据兰州市社会发展状况及前人的研究结果,分别分析了兰州市城市热岛强度在1971—1980年、1990—1995年和1997—2003年3个时段的季节变化规律,未来兰州夏季热岛效应将会排在第一位。运用灰色关联度分析法对影响兰州市城市热岛效应的因子群进行了贡献测度分析,结果表明,人为热释放是造成兰州市城市热岛效应的关键因素;风速、总云量是影响兰州市城市热岛效应的主要气象因子。最后通过改进GM(1,1)模型的拟合与预测,结果与实际情况具有良好一致性,表明兰州市城市热岛效应有进一步加重的趋势。     

Assessment of Urban Air Pollution and Spatial Spillover Effects in China: Cases of 113 Key Environmental Protection Cities

With rapid urbanization and energy consumption, environmental pollution and degradation have become increasingly serious problems in China. At the beginning of 2013, China implemented new ambient air quality standards (GB 3095-2012) in which the concentration of six pollutants including PM_2.5, ozone, carbon monoxide, PM₁₀, sulfur dioxide and nitrogen dioxide were monitored. This study gathered annual air pollutant concentration data for the six pollutants in 113 key environmental protection cites throughout China in 2014 and 2015 to explain spatial patterns of urban air pollution. Based on the Kernel density estimation method, spatial hotspots of air pollution were illustrated through which spatial cluster of each pollutants could be plotted. By employing an entropy evaluation system, urban air quality was assessed in terms of the six atmospheric pollutants. We conclude that, in general, CO and SO₂ were two important pollutants in most Chinese cities, but this varied greatly among cities. The assessment results indicate that cities with the worst air quality were mainly located in northern and central provinces, dominantly in the Beijing-Tianjin-Hebei metropolitan area. Regression modeling showed that a combination of meteorological factors and human-related determinants, to say specifically, industrialization and urbanization factors, greatly influenced urban air quality variation in China. Results from spatial lag regression modeling confirmed that air pollution existed obvious spatial spillover effects among key cities. The spatial interdependence effects of urban air quality means that Chinese municipal governments should strengthen regional cooperation and deepen bilateral collaboration in terms of air regulation and pollution prevention.     

半干旱区城市人工森林生态系统服务价值评估——以兰州市南北两山环境绿化工程区为例

基于2005年兰州市南北两山环境绿化工程区的卫星遥感资料,应用生态系统服务评价方法,结合研究区实际情况,对研究区的城市人工森林生态系统服务价值进行评估。结果表明:①2005年研究区的人工森林生态系统总服务价值为15.59亿元·a-1;各项服务价值的顺序依次为:森林游憩＞维持大气平衡＞涵养水源＞林副产品＞固土保肥＞保护生物多样性＞木材＞薪炭材;②城市人工森林生态系统服务价值组成上表现为经济效益（直接价值）与生态效益（间接价值）的比例相差不大,明显有异于自然生态系统,这主要是由人工生态系统的人为性和明确的目的性造成的。研究表明,城市人工生态系统对CO2减排的可持续性和生态安全具有现实意义。对积极探索西部地区的生物减排及水土资源及生态安全问题,对进行城市人工生态系统服务评价具有一定的借鉴意义。     

农牧交错带不同人工植被下荒漠化土壤肥力的变化

研究了陕北农牧交错带荒漠化土地上种植人工植被后,在不同的植被恢复类型和生长状态下土壤物理、化学和生物学性状的特征。结果表明,随着人工植被的建立与生长,土壤肥力总体趋于好转,土壤理化性质得到显著改善,土壤质地变细,微生物数量增加,土壤酶活性增强;同时,使流动沙地向半固定、固定沙丘方向转化。但随着植被盖度和植被种类的不同,不同样地土壤肥力差异很大;多年生乔木林改良土壤肥力的潜力最高,耕作粗放的农地土壤肥力有所下降。     

Prediction of Blast-Induced Ground Vibration in a Mine Using Relevance Vector Regression Optimized by Metaheuristic Algorithms

Natural Resources Research - Prediction of ground vibration induced by blasting operations is a crucial challenge to engineers working in surface mines. This study aims to assess the efficiency of...