The out-of-sample prediction error of the square-root-LASSO and related estimators

We study the classical problem of predicting an outcome variable, $Y$, using a linear combination of a $d$-dimensional covariate vector, $\mathbf{X}$. We are interested in linear predictors whose coefficients solve: % \begin{align*} \inf_{\boldsymbol{\beta} \in \mathbb{R}^d} \left( \mathbb{E}_{\mathbb{P}_n} \left[ \left(Y-\mathbf{X}^{\top}\beta \right)^r \right] \right)^{1/r} +\delta \, \rho\left(\boldsymbol{\beta}\right), \end{align*} where $\delta>0$ is a regularization parameter, $\rho:\mathbb{R}^d\to \mathbb{R}_+$ is a convex penalty function, $\mathbb{P}_n$ is the empirical distribution of the data, and $r\geq 1$. We present three sets of new results. First, we provide conditions under which linear predictors based on these estimators % solve a \emph{distributionally robust optimization} problem: they minimize the worst-case prediction error over distributions that are close to each other in a type of \emph{max-sliced Wasserstein metric}. Second, we provide a detailed finite-sample and asymptotic analysis of the statistical properties of the balls of distributions over which the worst-case prediction error is analyzed. Third, we use the distributionally robust optimality and our statistical analysis to present i) an oracle recommendation for the choice of regularization parameter, $\delta$, that guarantees good out-of-sample prediction error; and ii) a test-statistic to rank the out-of-sample performance of two different linear estimators. None of our results rely on sparsity assumptions about the true data generating process; thus, they broaden the scope of use of the square-root lasso and related estimators in prediction problems

Rate transient analysis and completion optimization study in Eagle Ford shale

Master's Project (M.S.) University of Alaska Fairbanks, 2015Analysis of well performance data can deliver decision-making solutions regarding field development, production optimization, and reserves evaluation. Well performance analysis involves the study of the measured response of a system, the reservoir in our case, in the form of production rates and flowing pressures. The Eagle Ford shale in South Texas is one of the most prolific shale plays in the United States. However, the ultra-low permeability of the shale combined with its limited production history makes predicting ultimate recovery very difficult, especially in the early life of a well. Use of Rate Transient Analysis makes the analysis of early production data possible, which involves solving an inverse problem. Unlike the traditional decline analysis, Rate Transient Analysis requires measured production rates and flowing pressures, which were provided by an operator based in the Eagle Ford. This study is divided into two objectives. The first objective is to analyze well performance data from Eagle Ford shale gas wells provided by an operator. This analysis adopts the use of probabilistic rate transient analysis to help quantify uncertainty. With this approach, it is possible to systematically investigate the allowable parameter space based on acceptable ranges of inputs such as fracture length, matrix permeability, conductivity and well spacing. Since well spacing and reservoir boundaries were unknown, a base case with a reservoir width of 1500 feet was assumed. This analysis presents a workflow that integrates probabilistic and analytical modeling for shale gas wells in an unconventional reservoir. To validate the results between probabilistic and analytical modeling, a percent difference of less than 15% was assumed as an acceptable range for the ultimate recoverable forecasts. Understanding the effect of existing completion on the cumulative production is of great value to operators. This information helps them plan and optimize future completion designs while reducing operational costs. This study addresses the secondary objective by generating an Artificial Neural Network model. Using database from existing wells, a neural network model was successfully generated and completion effectiveness and optimization analysis was conducted. A good agreement between the predicted model output values and actual values (R² = 0.99) validated the applicability of this model. A completion optimization study showed that wells drilled in condensate-rich zones required higher proppant and liquid volumes, whereas wells in gas-rich zones required closer cluster spacing. Analysis results helped to identify wells which were either under-stimulated or over-stimulated and appropriate recommendations were made

Shaped coil-core design for inductive energy collectors

Coil design is important for maximizing power density in inductive energy harvesting as well as in inductive power transfer. In this work, we present a study of coil performance, based on simulated flux distributions corresponding to a real aircraft application case. The use of funnel-shaped soft magnetic cores boosts magnetic flux density by flux concentration and allows the use of a smaller diameter coil. This reduces the transducer mass as well as the coil resistance (R COIL ), thereby increasing the power density. Analysis and simulation shows a fifty-fold power density increase from moderate funneling and another two-fold increase by coil size optimization. Results are compared with experimental measurements presented in [1] which demonstrate a 36μW/g(106μW/cm 3 ) power density from alternating environmental magnetic fields in the 10μT/300 Hz range

기구학적 특성과 컴플라이언스 특성을 동시에 고려한 기구 위상 및 형상 통합 최적설계

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 기계항공공학부(멀티스케일 기계설계전공), 2020. 8. 김윤영.Mechanism synthesis based on topology optimization has recently received much attention as an efficient design approach. The main thrust behind this trend is the capability of this method to determine automatically the topology and dimensions of linkage mechanisms. Towards this direction, there have been many investigations, but they have thus far focused mainly on mechanism synthesis considering kinematic characteristics describing a desired path or motion. Here, we propose a new topology optimization method that synthesizes a linkage mechanism considering not only kinematic but also compliance (K&C) characteristics simultaneously, as compliance characteristics can also significantly affect the linkage mechanism performance; compliance characteristics dictate how elastic components, such as bushings in a vehicle suspension, are deformed by external forces. To achieve our objective, we use the spring-connected rigid block model (SBM) developed earlier for mechanism synthesis considering only kinematic characteristics, but we make it suitable for the simultaneous consideration of K&C characteristics during mechanism synthesis by making its zero-length springs multifunctional. Variable-stiffness springs were used to identify the mechanism kinematic configuration only, but now in the proposed approach, they serve to determine not only the mechanism kinematic configuration but also the compliance element distribution. In particular, the ground-anchoring springs used to anchor a linkage mechanism to the ground are functionalized to simulate actual bushings as well as to identify the desired linkage kinematic chain. After the proposed formulation and numerical implementation are presented, three case studies to synthesize planar linkage mechanisms were considered. Through these case studies, we verified the validation of the proposed approach and proved that the proposed methodology could solve problems when existing methods could not. After the effectiveness of the proposed method is demonstrated with a simplified two-dimensional vehicle suspension design problem, the proposed methodology is applied to design a three-dimensional suspension. To deal with three-dimensional mechanisms, a spatial SBM is newly developed because only planar SBMs have been developed. Furthermore, a set of design variables which can vary bushing stiffness are newly introduced. Using the proposed method, it was possible to successfully synthesize two types of suspension mechanisms which have similar kinematic characteristics to each other but different compliance characteristics. By using the proposed method simultaneously considering kinematic and compliance characteristics, a unique suspension mechanism having an integral module which is known to improve R&H performances was synthesized. In this study, although applications were made only to the design of vehicle suspensions, other practical design problems for which K&C characteristics must be considered simultaneously can be also effectively solved by the proposed approach. This study is expected to pave the way to advance the topology optimization method for general linkage mechanisms considering kinematic characteristics but also the other characteristics such as force-related characteristics.위상 최적화(topology optimization) 기법을 이용한 한 기구 합성(mechanism synthesis)은 그 효율성으로 인해 최근 많은 주목을 받고 있다. 이러한 추세의 주 원인은 기구 위상 최적화 기법으로 인해 기구의 위상(topology)과 치수(dimension)를 자동으로 합성할 수 있기 때문이다. 이러한 방향성을 가지고 지금까지 많은 연구들이 진행되어 왔지만, 지금까지 진행된 연구들은 모두 경로 합성이나 운동 합성과 같이 기구학적 특성을 고려하는 데에만 관심이 집중되었다. 본 연구에서는 기구의 기구학적 특성(kinematic characteristics)과 컴플라이언스 특성(compliance characteristics)을 동시에 고려할 수 있는 새로운 기구 위상 최적화 기법을 제안한다. 기구학적 특성은 기구 설계에 있어 매우 중요한 특성이지만, 외력이 작용하였을 때 자동차 서스펜션(vehicle suspension)의 부싱(bushing)과 같은 탄성 요소들의 변형으로 인해 나타나는 컴플라이언스 특성 또한 기구 설계 시 고려해야 할 중요한 특성이기 때문이다. 새로운 기구 위상 최적화 기법을 위해 우리는 기구학적 특성만을 고려하기 위해 개발되었던 스프링-연결 블록 모델(spring-connected block model)을 기구학적 특성과 컴플라이언스 특성을 동시에 고려할 수 있도록 고안하였다. 기존의 스프링-연결 블록 모델에서는 기구학적 연결 관계만을 표현하는데 사용되던 가변 강성 스프링을 본 연구에서는 기구학적 연결 관계뿐 아니라 실제 부싱을 표현하도록 다목적으로 활용하여 기구학적 특성과 컴플라이언스 특성을 하나의 모델링을 통해 성공적으로 표현하였다. 개발한 방법론의 효과를 입증하기 위해 평면 기구 합성을 목표로 한 세 종류의 사례 연구(case study)를 진행하였고, 이러한 사례 연구를 통해 우리는 제안한 방법이 기존의 방법으로는 해결할 수 없는 문제 상황을 해결할 수 있음을 확인하였다. 개발한 방법론을 보다 실용적인 문제에 적용하기 위해 3차원 자동차 서스펜션(vehicle suspension) 설계 하고자 하였으며, 이를 위해 스프링-연결 블록 모델을 3차원으로 확장하였다. 또한, 보다 실용적인 설계 결과 도출을 위해 2차원 사례 연구에서는 사용하지 않았던 부싱 강성 조절 설계 변수를 추가적으로 도입하여, 부싱 강성도 동시에 설계를 진행하였다. 3차원 서스펜션 설계는 기구학적 조건은 동일하지만, 컴플라이언스 특성은 다른 두 가지 조건에 대해 진행되었으며, 두 설계 조건에서 모두 서스펜션 합성에 성공하였다. 특히, 두 서스펜션의 결과 위상이 서로 다른 것을 확인할 수 있었는데, 이를 통해 기구학적 조건은 동일하되 컴플라이언스 조건이 달라지면 결과 위상이 달라질 수 있음을 확인하였고, 개발한 방법론을 통해 설계 조건에 맞는 기구의 위상과 치수 그리고 필요한 부싱 강성까지도 성공적으로 설계할 수 있음을 증명하였다. 본 연구는 컴플라이언스 조건이 특히 중요시 되는 자동차 서스펜션을 설계하는데 집중하였지만, 개발한 방법론은 기구학적 특성과 컴플라이언스 특성이 모두 요구되는 다른 설계 문제에도 적용될 수 있을 것으로 기대된다. 또한, 이 연구는 기구학적 특성뿐만 아니라 힘과 관련된 다른 특성을 고려한 일반적인 기구 위상 최적화 기법으로의 발전에 기여할 것으로 기대된다.CHAPTER 1. Introduction 1 1.1 Motivation and related literatures 1 1.2 Research objectives 6 1.3 Background research 8 1.3.1 Linkage mechanism synthesis based on the spring-connected rigid block model (SBM) 8 1.3.2 Determination of the systems degree-of-freedom (DOF) based on the work transmittance efficiency function 10 1.4 Outline of thesis 12 CHAPTER 2. Unified topology and shape optimization method for the mechanism synthesis simultaneously considering kinematic and compliance (K&C) characteristics 18 2.1 Overview 18 2.2 Modeling and analysis 23 2.2.1 Modeling 23 2.2.2 Kinematic and compliance analyses with the SBM 26 2.3 Optimization Formulation 33 2.3.1 Design variable and interpolation 33 2.3.2 Objective and constraint functions 35 2.3.3 Sensitivity analysis 39 2.4 Case studies 43 2.4.1 Case study 1 - Validation of the proposed method 43 2.4.2 Case study 2 - Demonstration of the advantage of the proposed method 46 2.4.3 Case study 3 - Application to the design of a 2D vehicle suspension 50 2.5 Summary 57 CHAPTER 3. Design of vehicle suspensions for rear using topology optimization method considering K&C characteristics 78 3.1 Overview 78 3.2 Modeling and analysis based on the spatial SBM 81 3.2.1 The spatial SBM for the design of a vehicle suspension 81 3.2.2 Kinematic and compliance analyses by the spatial SBM 83 3.3 Optimization Formulation 90 3.3.1 Design variable and interpolation 90 3.3.2 Objective and constraint functions 93 3.3.3 Sensitivity analysis 95 3.4 Design of vehicle suspensions for rear using the proposed method 99 3.4.1 Definition of problem 99 3.4.2 Design Case 1 - Recovery of a double wishbone suspension 101 3.4.3 Design Case 2 - Suspension synthesis for improving ride and handling (R&H) performances 104 3.5 Summary 110 CHAPTER 4. Conclusions 133 APPENDIX A. Target cascading process for deriving K&C characteristics of a suspension to improve vehicles R&H performances 138 A.1 Overview 138 A.2 Ride and handling (R&H) performances 139 A.3 Analysis procedure to evaluate R&H performances using a double wishbone suspension 140 A.4 Design optimization of a double wishbone suspension for deriving K&C characteristics to improve R&H performances 141 A.4.1 Design variable and interpolation 141 A.4.2 Metamodeling 142 A.4.3 Optimization formulation 144 A.4.4 Optimization result 145 APPENDIX B. Technique to suppress floating blocks 158 B.1 Overview 158 B.2 Explanation of techniques to suppress floating blocks 159 B.3 Revisit Case study 3 for applying the technique to suppress floating blocks 161 APPENDIX C. Investigation of mesh dependency issue 167 C.1 Overview 167 C.2 Re-consideration of Case study 1 with the more number of rigid blocks 168 REFERENCES 172 ABSTRACT (KOREAN) 181 ACKNOWLEDTEMENTS 184Docto

Embodied Energy Optimization of Buttressed Earth-Retaining Walls with Hybrid Simulated Annealing

[EN] The importance of construction in the consumption of natural resources is leading structural design professionals to create more efficient structure designs that reduce emissions as well as the energy consumed. This paper presents an automated process to obtain low embodied energy buttressed earth-retaining wall optimum designs. Two objective functions were considered to compare the difference between a cost optimization and an embodied energy optimization. To reach the best design for every optimization criterion, a tuning of the algorithm parameters was carried out. This study used a hybrid simulated optimization algorithm to obtain the values of the geometry, the concrete resistances, and the amounts of concrete and materials to obtain an optimum buttressed earth-retaining wall low embodied energy design. The relation between all the geometric variables and the wall height was obtained by adjusting the linear and parabolic functions. A relationship was found between the two optimization criteria, and it can be concluded that cost and energy optimization are linked. This allows us to state that a cost reduction of €1 has an associated energy consumption reduction of 4.54 kWh. To achieve a low embodied energy design, it is recommended to reduce the distance between buttresses with respect to economic optimization. This decrease allows a reduction in the reinforcing steel needed to resist stem bending. The difference between the results of the geometric variables of the foundation for the two-optimization objectives reveals hardly any variation between them. This work gives technicians some rules to get optimum cost and embodied energy design. Furthermore, it compares designs obtained through these two optimization objectives with traditional design recommendations.The authors acknowledge the financial support of the Spanish Ministry of Economy and Business, along with FEDER funding (DIMALIFE Project: BIA2017-85098-R) and the Spanish Ministry of Science, Innovation and Universities for David Martínez-Muñoz University Teacher Training Grant (FPU18/01592). They would also like to emphasize that José García was supported by the Grant CONICYT/FONDECYT/INICIACION/11180056.Martínez-Muñoz, D.; Martí Albiñana, JV.; García, J.; Yepes, V. (2021). Embodied Energy Optimization of Buttressed Earth-Retaining Walls with Hybrid Simulated Annealing. Applied Sciences. 11(4):1-16. https://doi.org/10.3390/app11041800S116114Casals, X. G. (2006). Analysis of building energy regulation and certification in Europe: Their role, limitations and differences. 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Engineering Applications of Artificial Intelligence, 19(5), 557-567. doi:10.1016/j.engappai.2005.12.00

Contractivity of neural ODEs: an eigenvalue optimization problem

We propose a novel methodology to solve a key eigenvalue optimization problem which arises in the contractivity analysis of neural ODEs. When looking at contractivity properties of a one layer weight-tied neural ODE $\dot{u}(t)=\sigma(Au(t)+b)$ (with $u,b \in {\mathbb R}^n$, $A$ is a given $n \times n$ matrix, $\sigma : {\mathbb R} \to {\mathbb R}^+$ denotes an activation function and for a vector $z \in {\mathbb R}^n$, $\sigma(z) \in {\mathbb R}^n$ has to be interpreted entry-wise), we are led to study the logarithmic norm of a set of products of type $D A$, where $D$ is a diagonal matrix such that ${\mathrm{diag}}(D) \in \sigma'({\mathbb R}^n)$. Specifically, given a real number $c$ (usually $c=0$), the problem consists in finding the largest positive interval $\chi\subseteq \mathbb [0,\infty)$ such that the logarithmic norm $\mu(DA) \le c$ for all diagonal matrices $D$ with $D_{ii}\in \chi$. We propose a two-level nested methodology: an inner level where, for a given $\chi$, we compute an optimizer $D^\star(\chi)$ by a gradient system approach, and an outer level where we tune $\chi$ so that the value $c$ is reached by $\mu(D^\star(\chi)A)$. We extend the proposed two-level approach to the general multilayer, and possibly time-dependent, case $\dot{u}(t) = \sigma( A_k(t) \ldots \sigma ( A_{1}(t) u(t) + b_{1}(t) ) \ldots + b_{k}(t) )$ and we propose several numerical examples to illustrate its behaviour, including its stabilizing performance on a one-layer neural ODE applied to the classification of the MNIST handwritten digits dataset.Comment: 23 pages, 5 figures, 3 table

Integrated asset management system for performance-based road maintenance contracts

Performance-based maintenance contracts (PBMC) for highways are increasingly becoming an attractive mechanism for transferring activities traditionally undertaken by the public sector to private entities. Increased financial pressures on governments, demands for improved service levels by highway users, and the operational efficiencies offered by the private sector, all create a strong business case for PBMC. In order to enable government road agencies and private sector investors to engage in the use of PBMC, there is a need for quantitative tools that allow both entities to 1) Properly structure the PBMC in terms of risk allocation, 2) Develop appropriate levels for service level penalties and incentives in the contract, 3) Determine appropriate targets for highway level of service, and 4) Determine the most cost-effective set of road maintenance and rehabilitation (M&R) activities to be undertaken throughout the duration of the contract. This research developed a GIS-based Integrated Highway Asset Management System (IHAMS), which extends typical functionality of traditional pavement management systems to cover specific contractual requirements of PBMC. The system allows the analysis of both network-level and project-level asset management decisions. Defect-specific pavement deterioration models are developed using multivariate regression. Stochastic network-level deterioration models are developed using markov chains. Life cycle costing models are developed to cover specific financial obligations in PBMC like penalties and incentives, in addition to traditional M&R expenditure. A GA-based optimization modules is used to trade-off various decision scenarios that are beneficial to both road maintenance contracts and road agencies. A case study for the Cairo-Ismalliyah desert highway is used to demonstrate the capability of the system

Analytical Methodology for the Identification of Critical Zones on the Generation of Solid Waste in Large Urban Areas

[EN] One of the main environmental issues to address in large urban areas is the ever-increasing generation of municipal solid waste (MSW) and the need to manage it properly. Despite significant efforts having been made to implement comprehensive solid waste management systems, current management methods often do not provide sustainable alternatives which ensure the reduction of solid waste generation. This paper presents an analytical methodology that employs a combination of geographic information system techniques (GIS) along with statistical and numerical optimization methods to evaluate solid waste generation in large urban areas. The methodology was successfully applied to evaluate MSW generation in different exclusive service areas (ASES) of the city of Bogotá (Colombia). The results of the analysis on the solid waste generation data in each collection area in terms of its socioeconomic level are presented below. These socioeconomic levels are explained by defining different strata in terms of their purchasing power. The results demonstrate the usefulness of these GIS and numerical optimization techniques as a valuable complementary tool to analyze and design efficient and sustainable solid waste management systems.Thanks are due to the Final Disposal Area of the Special Administrative Unit of Public Services of Bogotá for their support in providing data to perform this research studySolano-Meza, J.; Rodrigo-Ilarri, J.; Romero-Hernandez, CP.; Rodrigo-Clavero, M. (2020). Analytical Methodology for the Identification of Critical Zones on the Generation of Solid Waste in Large Urban Areas. International Journal of Environmental research and Public Health. 17(4):1-14. https://doi.org/10.3390/ijerph17041196S114174Vitorino de Souza Melaré, A., Montenegro González, S., Faceli, K., & Casadei, V. (2017). Technologies and decision support systems to aid solid-waste management: a systematic review. 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Resources, Conservation and Recycling, 154, 104625. doi:10.1016/j.resconrec.2019.104625Singh, A. (2019). Solid waste management through the applications of mathematical models. Resources, Conservation and Recycling, 151, 104503. doi:10.1016/j.resconrec.2019.104503Dehghanifard, E., & Dehghani, M. H. (2018). Evaluation and analysis of municipal solid wastes in Tehran, Iran. MethodsX, 5, 312-321. doi:10.1016/j.mex.2018.04.003Lella, J., Mandla, V. R., & Zhu, X. (2017). Solid waste collection/transport optimization and vegetation land cover estimation using Geographic Information System (GIS): A case study of a proposed smart-city. Sustainable Cities and Society, 35, 336-349. doi:10.1016/j.scs.2017.08.023Zysk, E., Dawidowicz, A., Źróbek, S., & Źróbek, R. (2020). The concept of a geographic information system for the identification of degraded urban areas as a part of the land administration system - A Polish case study. Cities, 96, 102423. doi:10.1016/j.cities.2019.102423Ferronato, N., Preziosi, G., Gorritty Portillo, M. A., Guisbert Lizarazu, E. G., & Torretta, V. (2020). Assessment of municipal solid waste selective collection scenarios with geographic information systems in Bolivia. Waste Management, 102, 919-931. doi:10.1016/j.wasman.2019.12.010Erfani, S. M. H., Danesh, S., Karrabi, S. M., Gheibi, M., & Nemati, S. (2019). Statistical analysis of effective variables on the performance of waste storage service using geographical information system and response surface methodology. Journal of Environmental Management, 235, 453-462. doi:10.1016/j.jenvman.2019.01.061Murray, A. T. (2019). Contemporary optimization application through geographic information systems. Omega, 102176. doi:10.1016/j.omega.2019.102176Ghinea, C., Drăgoi, E. N., Comăniţă, E.-D., Gavrilescu, M., Câmpean, T., Curteanu, S., & Gavrilescu, M. (2016). Forecasting municipal solid waste generation using prognostic tools and regression analysis. Journal of Environmental Management, 182, 80-93. doi:10.1016/j.jenvman.2016.07.026Singh, D., & Satija, A. (2016). Prediction of municipal solid waste generation for optimum planning and management with artificial neural network—case study: Faridabad City in Haryana State (India). International Journal of System Assurance Engineering and Management, 9(1), 91-97. doi:10.1007/s13198-016-0484-5Nguyen-Trong, K., Nguyen-Thi-Ngoc, A., Nguyen-Ngoc, D., & Dinh-Thi-Hai, V. (2017). Optimization of municipal solid waste transportation by integrating GIS analysis, equation-based, and agent-based model. Waste Management, 59, 14-22. doi:10.1016/j.wasman.2016.10.048Malakahmad, A., Bakri, P. M., Mokhtar, M. R. M., & Khalil, N. (2014). Solid Waste Collection Routes Optimization via GIS Techniques in Ipoh City, Malaysia. Procedia Engineering, 77, 20-27. doi:10.1016/j.proeng.2014.07.023Gbanie, S. P., Tengbe, P. B., Momoh, J. S., Medo, J., & Kabba, V. T. S. (2013). Modelling landfill location using Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA): Case study Bo, Southern Sierra Leone. Applied Geography, 36, 3-12. doi:10.1016/j.apgeog.2012.06.013Al-Salem, S. M., Al-Nasser, A., & Al-Dhafeeri, A. T. (2018). Multi-variable regression analysis for the solid waste generation in the State of Kuwait. Process Safety and Environmental Protection, 119, 172-180. doi:10.1016/j.psep.2018.07.017Duan, N., Li, D., Wang, P., Ma, W., Wenga, T., Zhong, L., & Chen, G. (2020). Comparative study of municipal solid waste disposal in three Chinese representative cities. Journal of Cleaner Production, 254, 120134. doi:10.1016/j.jclepro.2020.120134Niska, H., & Serkkola, A. (2018). Data analytics approach to create waste generation profiles for waste management and collection. Waste Management, 77, 477-485. doi:10.1016/j.wasman.2018.04.033Solano Meza, J. K., Orjuela Yepes, D., Rodrigo-Ilarri, J., & Cassiraga, E. (2019). Predictive analysis of urban waste generation for the city of Bogotá, Colombia, through the implementation of decision trees-based machine learning, support vector machines and artificial neural networks. Heliyon, 5(11), e02810. doi:10.1016/j.heliyon.2019.e0281