Relevant bibliographies by topics / Spatial-Dynamic Optimization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Spatial-Dynamic Optimization'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Spatial-Dynamic Optimization"

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Jeong, Hanbat, and Lung-fei Lee. "Spatial dynamic models with intertemporal optimization: Specification and estimation." Journal of Econometrics 218, no. 1 (2020): 82–104. http://dx.doi.org/10.1016/j.jeconom.2019.10.012.

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Zhu, Nanhai, and Jinlei Liu. "Multiobjective Topology Optimization of Spatial-Structure Joints." Advances in Civil Engineering 2021 (April 10, 2021): 1–13. http://dx.doi.org/10.1155/2021/5530644.

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To realize the static and dynamic multiobjective topology optimization of joints in spatial structures, structural topology optimization is carried out to maximize the stiffness under static multiload conditions and maximize the first third-order dynamic natural frequencies. According to the single-objective optimization results, the objective function of the multiobjective topology optimization of joints is established by using the compromise programming method, and the weight coefficient of each static load condition is determined by using the analytic hierarchy process. Subsequently, under
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TORII, Takao, Kazufumi WATANABE, Bin Fen, and Nobuyoshi MORITA. "Optimization of Link Shape on Dynamic Design of Spatial RSSR Mechanism." Proceedings of the JSME annual meeting 2004.4 (2004): 167–68. http://dx.doi.org/10.1299/jsmemecjo.2004.4.0_167.

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Zhu, Yong Yong, and S. Y. Gao. "Optimization Research on Dynamic Balance of Spatial Engine under Limiting Shaking Moment." Materials Science Forum 626-627 (August 2009): 693–98. http://dx.doi.org/10.4028/www.scientific.net/msf.626-627.693.

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Dynamic balance of the spatial engine is researched. By considering the special wobble-plate engine as the model of spatial RRSSC linkages, design variables on the engine structure are confirmed based on the configuration characters and kinetic analysis of wobble-plate engine. In order to control the vibration of the engine frame and to decrease noise caused by the spatial engine, objective function is choosed as the dimensionless combinations of the various shaking forces and moments, the restriction condition of which presents limiting the percent of shaking moment. Then the optimization des
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Zeng, Mingbin, Xu Yang, Mengxing Wang, and Bangjiang Xu. "Application of Angle Related Cost Function Optimization for Dynamic Path Planning Algorithm." Algorithms 11, no. 8 (2018): 127. http://dx.doi.org/10.3390/a11080127.

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In recent years, Intelligent Transportation Systems (ITS) have developed a lot. More and more sensors and communication technologies (e.g., cloud computing) are being integrated into cars, which opens up a new design space for vehicular-based applications. In this paper, we present the Spatial Optimized Dynamic Path Planning algorithm. Our contributions are, firstly, to enhance the effective of loading mechanism for road maps by dividing the connected sub-net, and building a spatial index; and secondly, to enhance the effect of the dynamic path planning by optimizing the search direction. We u
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Nurullah, A. M. M., Glen A. Jordan, and Emin Zeki Baskent. "Spatial stratification in forest modelling." Forestry Chronicle 76, no. 2 (2000): 311–17. http://dx.doi.org/10.5558/tfc76311-2.

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This paper discusses the concept of spatial stratification (SS) as applied to forest modelling in general, and spatial forest modelling in particular. SS is a way of providing a geographically explicit forest description in forest modelling, or a way of accommodating spatially explicit management objectives and interventions. In the former, called a priori SS, stands of a forest landscape are spatially aggregated into a set of stand clusters which become input to forest modelling. The latter, called dynamic SS, utilizes stands as the input forest description upon which various spatial aggregat
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Speir, Cameron, Jae Han, and Nicholas Brozović. "Spatial Dynamic Optimization of Groundwater Use with Ecological Standards for Instream Flow." Water Economics and Policy 02, no. 03 (2016): 1650013. http://dx.doi.org/10.1142/s2382624x16500132.

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We examine how variations in the spatial distribution and timing of groundwater management actions, as well as the physical characteristics of a stream aquifer system, affect regulators’ ability to meet instream goals in a stream-aquifer system. We propose an optimization model that distributes restrictions on groundwater pumping among a set of irrigators in a way that minimizes costs, subject to meeting instream flow requirements. Our model is distinguished by two features: (1) instream flow requirements must be met daily and (2) we incorporate a hydrologic model of stream-aquifer interaction
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Jeong, Hanbat, and Lung-fei Lee. "Spatial dynamic game models for coevolution of intertemporal economic decision-making and spatial networks." Journal of Economic Dynamics and Control 129 (August 2021): 104186. http://dx.doi.org/10.1016/j.jedc.2021.104186.

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Shen, Dingcai, Bei Qian, and Min Wang. "A Species Conservation-Based Particle Swarm Optimization with Local Search for Dynamic Optimization Problems." Computational Intelligence and Neuroscience 2020 (August 1, 2020): 1–10. http://dx.doi.org/10.1155/2020/2815802.

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In the optimization of problems in dynamic environments, algorithms need to not only find the global optimal solutions in a specific environment but also to continuously track the moving optimal solutions over dynamic environments. To address this requirement, a species conservation-based particle swarm optimization (PSO), combined with a spatial neighbourhood best searching technique, is proposed. This algorithm employs a species conservation technique to save the found optima distributed in the search space, and these saved optima either transferred into the new population or replaced by the
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Chen, Xiu Long, Shuai Shuai Jia, Chong Jie Du, and Shi Bo Shen. "Elastic Dynamics Optimization Design of Novel High-Speed Spatial Parallel Robot." Advanced Materials Research 415-417 (December 2011): 39–42. http://dx.doi.org/10.4028/www.scientific.net/amr.415-417.39.

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In order to improve performance of 4-UPS-RPS high-speed spatial parallel robot, the elastic dynamics optimization design was executed. The influence law of the mass of moving platform and the diameter of driving limbs on the dynamic performance, which includes kinematics output response and maximum dynamic stress of driving limbs, were discussed. On these grounds, the mass of moving platform and the diameter of driving limbs were optimized. The simulation results show obvious improvement of the dynamics performance for 4-UPS-RPS parallel robot, therefore the theoretical basis are provided.
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Dissertations / Theses on the topic "Spatial-Dynamic Optimization"

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Jeong, Hanbat. "Spatial dynamic models with intertemporal optimization." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1556308178720915.

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Goodenberger, James Stevenson. "Three Essays Regarding the Economics of Resources with Spatial-Dynamic Transition Processes." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1468964324.

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Phunchongharn, Phond. "Dynamic wireless access methods with applications to eHealth services." IEEE, 2009. http://hdl.handle.net/1993/9231.

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For opportunistic spectrum access and spectrum sharing in cognitive radio networks, one key problem is how to develop wireless access schemes for secondary users so that harmful interference to primary users can be avoided and quality-of-service (QoS) of secondary users can be guaranteed. In this research, dynamic wireless access protocols for secondary users are designed and optimized for both infrastructure-based and ad-hoc wireless networks. Under the infrastructure-based model, the secondary users are connected through a controller (i.e., an access point). In particular, the problem
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Charles, Adam Shabti. "Dynamics and correlations in sparse signal acquisition." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53592.

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One of the most important parts of engineered and biological systems is the ability to acquire and interpret information from the surrounding world accurately and in time-scales relevant to the tasks critical to system performance. This classical concept of efficient signal acquisition has been a cornerstone of signal processing research, spawning traditional sampling theorems (e.g. Shannon-Nyquist sampling), efficient filter designs (e.g. the Parks-McClellan algorithm), novel VLSI chipsets for embedded systems, and optimal tracking algorithms (e.g. Kalman filtering). Traditional techniques h
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Nassir, Neema. "Optimal Integrated Dynamic Traffic Assignment and Signal Control for Evacuation of Large Traffic Networks with Varying Threat Levels." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/297042.

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This research contributes to the state of the art and state of the practice in solving a very important and computationally challenging problem in the areas of urban transportation systems, operations research, disaster management, and public policy. Being a very active topic of research during the past few decades, the problem of developing an efficient and practical strategy for evacuation of real-sized urban traffic networks in case of disasters from different causes, quickly enough to be employed in immediate disaster management scenarios, has been identified as one of the most challenging
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Campos-Candela, Andrea. "Linking individual behaviour and life history: bioenergetic mechanisms, eco-evolutionary outcomes and management implications." Doctoral thesis, Universidad de Alicante, 2019. http://hdl.handle.net/10045/89047.

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Animal behaviour is a state variable of the individual that deserves special attention given its determinant role in eco-evolutionary processes (Wolf et al. 2007 in Nature). The decomposition of the behavioural variation in between- and within-individual variability has revealed the existence of consistent between-individual differences referred to as personality or behavioural types (Dall et al. 2004 in Ecology Letters). Five axes of personality are usually recognized (exploration, aggressiveness, activity, sociability and boldness), and individual specificities along them tend to be correlat
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Cheng, Hung-Chih, and 鄭弘志. "Spatial Optimization and Dynamic Model for Marine Protected Area Planning." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/62422928307137634462.

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博士<br>國立中山大學<br>海洋環境及工程學系研究所<br>104<br>The systematic approach had been recognized as one of the most effective tools for Marine Protected Area (MPA) planning. But MPA planning still exist many uncertainty in the real world, ex. the effect of MPA planning and the support of stakeholders or neighbors. In recent years, there are many researches using Spatial Optimization Model for MPA planning, but only can provide “current optimal results” for decision marker. Decision marker couldn’t know the real effectiveness of MPA in the future, and stakeholders also couldn’t know their benefit would be af
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Sharma, G. K. "Multireservoir Systems Optimization : A New Approach." Thesis, 1995. http://etd.iisc.ernet.in/handle/2005/2194.

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Rasheed, Md Muhibur. "Predicting multibody assembly of proteins." Thesis, 2014. http://hdl.handle.net/2152/26149.

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This thesis addresses the multi-body assembly (MBA) problem in the context of protein assemblies. [...] In this thesis, we chose the protein assembly domain because accurate and reliable computational modeling, simulation and prediction of such assemblies would clearly accelerate discoveries in understanding of the complexities of metabolic pathways, identifying the molecular basis for normal health and diseases, and in the designing of new drugs and other therapeutics. [...] [We developed] F²Dock (Fast Fourier Docking) which includes a multi-term function which includes both a statistical the
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Book chapters on the topic "Spatial-Dynamic Optimization"

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Almonacid, Boris. "Simulation of a Dynamic Prey-Predator Spatial Model Based on Cellular Automata Using the Behavior of the Metaheuristic African Buffalo Optimization." In Natural and Artificial Computation for Biomedicine and Neuroscience. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59740-9_17.

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García-Pérez, Lía, María C. García-Alegre, Ángela Ribeiro, Domingo Guinea, and Jose María Cañas. "Perception and Tracking of Dynamic Objects for Optimization of Avoidance Strategies in Autonomous Piloting of Vehicles." In Spatial Cognition IV. Reasoning, Action, Interaction. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-32255-9_27.

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"Preliminary development of dynamic spatial models." In Integrated Urban Models Volume 2: New Research and Applications of Optimization and Dynamics (Routledge Revivals). Routledge, 2014. http://dx.doi.org/10.4324/9781315795652-18.

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"Conclusion: next research steps for dynamic spatial models." In Integrated Urban Models Volume 2: New Research and Applications of Optimization and Dynamics (Routledge Revivals). Routledge, 2014. http://dx.doi.org/10.4324/9781315795652-19.

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Bauer, S., and G. Schiefer. "PLANNING OF NATIONAL AGRICULTURAL INVESTMENT POLICIES WITH A DYNAMIC SPATIAL OPTIMIZATION MODEL – CASE, MODEL, EXPERIENCES." In Dynamic Modelling and Control of National Economies 1986. Elsevier, 1987. http://dx.doi.org/10.1016/b978-0-08-034795-0.50039-5.

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Kumarasamy, Umamaheswari, G. V. Shrichandran, and A. Vedanth Srivatson. "Diffuse Optical Tomography System in Soft Tissue Tumor Detection." In Digital Image Processing - Advances and Applications [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98708.

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Topical review of recent trends in Modeling and Regularization methods of Diffuse Optical Tomography (DOT) system promotes the optimization of the forward and inverse modeling methods which provides a 3D cauterization at a faster rate of 40frames/second with the help of a laser torch as a hand-held device. Analytical, Numerical and Statistical methods are reviewed for forward and inverse models in an optical imaging modality. The advancement in computational methods is discussed for forward and inverse models along with Optimization techniques using Artificial Neural Networks (ANN), Genetic Algorithm (GA) and Artificial Neuro Fuzzy Inference System (ANFIS). The studies carried on optimization techniques offers better spatial resolution which improves quality and quantity of optical images used for morphological tissues comparable to breast and brain in Near Infrared (NIR) light. Forward problem is based on the location of sources and detectors solved statistically by Monte Carlo simulations. Inverse problem or closeness in optical image reconstruction is moderated by different regularization techniques to improve the spatial and temporal resolution. Compared to conventional methods the ANFIS structure of optimization for forward and inverse modeling provides early detection of Malignant and Benign tumor thus saves the patient from the mortality of the disease. The ANFIS technique integrated with hardware provides the dynamic 3D image acquisition with the help of NIR light at a rapid rate. Thereby the DOT system is used to continuously monitor the Oxy and Deoxyhemoglobin changes on the tissue oncology.
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Abualhaol, Ibrahim Y., and Mustafa M. Matalgah. "Throughput Optimization of Cooperative Teleoperated UGV Network." In Innovations in Mobile Multimedia Communications and Applications. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-60960-563-6.ch007.

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Cooperative communications among group of teleoperated unmanned ground vehicles (UGVs) allows to exploit spatial diversity in wireless fading channels by relaying signals between each other. Due to the high speed of the UGVs, the nature of the channel environments and the possible co-channel interference, the effect of multipath propagation and the Doppler spread are more pronounced. In this article, we proposed a low complexity dynamic channel assignment (DCA) technique with adaptive modulation and coding (AMC) strategy to allocate the available bandwidth over a number of communications links in a cooperative UGV network. In many processing algorithms and transmission protocols reported in the literature, performance improvement in terms of system throughput and reliability has been demonstrated. The proposed DCA with AMC in a cooperative UGV network has two objectives. First, to maximize the overall throughput of the cooperative UGV network and second, to significantly reduce the probability of outage in the system. In this article, the outage is defined as the percentage of time the links are incapable of supporting a minimum required transmission rate which is determined by the application. The DCA approach is formulated in terms of a binary optimization problem that is solved using the branch-and-bound method. The authors assum the links in the network to be Rayleigh faded and we used a finite state Markov chain (FSMC) for their modeling. Using Monte Carlo simulation, we showed that the proposed DCA approach in a cooperative UGVs provides significant gain in the overall throughput and reduction in the outage probability compared to the static channel assignment (SCA).
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Cai, Tianxing. "Application of Biologically Inspired Techniques for Industrial and Environmental Research via Air Quality Monitoring Network." In Advances in Data Mining and Database Management. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6078-6.ch013.

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Industrial and environmental research will always involve the study of the cause-effect relationship between the emissions and the surrounding environment. Qualitative and mixed methods researchers have employed a variety of Information and Communication Technology (ICT) tools, simulated or virtual environments, information systems, information devices, and data analysis tools in this field. Machine-enhanced analytics has enabled the identification of aspects of interest such as correlations and anomalies from large datasets. Chemical facilities have high risks to originate air emission events. Based on an available air-quality monitoring network, the data integration technologies are applied to identify the scenarios of the possible emission source and the dynamic pollutant monitor result, so as to timely and effectively support diagnostic and prognostic decisions. In this chapter, the application of artificial neural networks for such applications have been developed according to the real application purpose. It includes two stages of modeling and optimization work: 1) the determination of background normal emission rates from multiple emission sources and 2) single-objective or multi-objective optimization for impact scenario identification and quantification. They have the capability to identify the potential emission profile and spatial-temporal characterization of pollutant dispersion for a specific region, including reverse estimation of the air quality issues. The methodology provides valuable information for accidental investigations and root cause analysis for an emission event; meanwhile, it helps evaluate the regional air quality impact caused by such an emission event as well. Case studies are employed to demonstrate the efficacy of the developed methodology.
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Gavrilova, M. L. "Adaptive Algorithms for Intelligent Geometric Computing." In Machine Learning. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-60960-818-7.ch109.

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This chapter spans topics from such important areas as Artificial Intelligence, Computational Geometry and Biometric Technologies. The primary focus is on the proposed Adaptive Computation Paradigm and its applications to surface modeling and biometric processing. Availability of much more affordable storage and high resolution image capturing devices have contributed significantly over the past few years to accumulating very large datasets of collected data (such as GIS maps, biometric samples, videos etc.). On the other hand, it also created significant challenges driven by the higher than ever volumes and the complexity of the data, that can no longer be resolved through acquisition of more memory, faster processors or optimization of existing algorithms. These developments justified the need for radically new concepts for massive data storage, processing and visualization. To address this need, the current chapter presents the original methodology based on the paradigm of the Adaptive Geometric Computing. The methodology enables storing complex data in a compact form, providing efficient access to it, preserving high level of details and visualizing dynamic changes in a smooth and continuous manner. The first part of the chapter discusses adaptive algorithms in real-time visualization, specifically in GIS (Geographic Information Systems) applications. Data structures such as Real-time Optimally Adaptive Mesh (ROAM) and Progressive Mesh (PM) are briefly surveyed. The adaptive method Adaptive Spatial Memory (ASM), developed by R. Apu and M. Gavrilova, is then introduced. This method allows fast and efficient visualization of complex data sets representing terrains, landscapes and Digital Elevation Models (DEM). Its advantages are briefly discussed. The second part of the chapter presents application of adaptive computation paradigm and evolutionary computing to missile simulation. As a result, patterns of complex behavior can be developed and analyzed. The final part of the chapter marries a concept of adaptive computation and topology-based techniques and discusses their application to challenging area of biometric computing.
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Cai, Tianxing. "Data Integration Technology for Industrial and Environmental Research via Air Quality Monitoring Network." In Enhancing Qualitative and Mixed Methods Research with Technology. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6493-7.ch007.

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Industrial and environmental research will always involve the study of the cause-effect relationship between emissions and the surrounding environment. Qualitative and mixed methods researchers have employed a variety of Information and Communication Technology (ICT) tools, simulated or virtual environments, information systems, information devices, and data analysis tools in this field. With the collection and representation of information in a range of ways, software tools have been created to manage and store this data. This data management enables more efficient searching ability of various types of electronic and digitized information. Various technologies have made the work of research more efficient. The results of the qualitative or mixed methods research may be integrated to reach the research target. Right now, a lot of software tools are available for analysis to identify patterns and represent new meanings. The programs extend the capabilities of the researcher in terms of information coding and meaning-making. Machine-enhanced analytics has enabled the identification of aspects of interest such as correlations and anomalies from large datasets. Chemical facilities, where large amounts of chemicals and fuels are processed, manufactured, and housed, have high risks to originate air emission events, such as intensive flaring and toxic gas release caused by various uncertainties like equipment failure, false operation, nature disaster, or terrorist attack. Based on an available air-quality monitoring network, the data integration technologies are applied to identify the scenarios of the possible emission source and the dynamic pollutant monitor result, so as to timely and effectively support diagnostic and prognostic decisions. In this chapter, several systematic methodologies and preliminary data integration system designs for such applications are developed according to the real application purpose. It includes two stages of modeling and optimization work: 1) the determination of background normal emission rates from multiple emission sources and 2) single-objective or multi-objective optimization for impact scenario identification and quantification. They have the capability of identifying the potential emission profile and spatial-temporal characterization of pollutant dispersion for a specific region, including reverse estimation of air quality issues. The chapter provides valuable information for accidental investigations and root cause analysis for an emission event, and it helps evaluate the regional air quality impact caused by such an emission event as well. Case studies are employed to demonstrate the efficacy of the developed methodology.
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Conference papers on the topic "Spatial-Dynamic Optimization"

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Xiong, Haitao, and Dan Wang. "Dynamic path optimization algorithm based on spatial-temporal and genetic factor." In 2016 13th International Conference on Service Systems and Service Management (ICSSSM). IEEE, 2016. http://dx.doi.org/10.1109/icsssm.2016.7538626.

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Moulard, Thomas, Eiichi Yoshida, and Shin'ichiro Nakaoka. "Optimization-based motion retargeting integrating spatial and dynamic constraints for humanoid." In 2013 44th International Symposium on Robotics (ISR). IEEE, 2013. http://dx.doi.org/10.1109/isr.2013.6695715.

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Monga, Vishal, and Umamahesh Srinivas. "A constrained optimization perspective on joint spatial resolution and dynamic range enhancement." In 2010 44th Asilomar Conference on Signals, Systems and Computers. IEEE, 2010. http://dx.doi.org/10.1109/acssc.2010.5757691.

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Lee, Byoungho, Hwi Kim, Joonku Hahn, and Kyongsik Choi. "Optimization of the beam shaping with a dynamic phase spatial light modulator." In Optics & Photonics 2005, edited by Fred M. Dickey and David L. Shealy. SPIE, 2005. http://dx.doi.org/10.1117/12.615578.

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Chi, Peng, Kaiwen Zhu, Jianjun Li, Wei Ai, Jing Huang, and Dongsheng Qing. "Dynamic Multi-Objective Optimization Model for Forest Spatial Structure with Environmental Detection Mechanism." In 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2019. http://dx.doi.org/10.1109/hpcc/smartcity/dss.2019.00224.

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Kakatsios, A. J., and S. J. Tricamo. "Integrated Kinematic and Dynamic Optimal Synthesis of Spatial Mechanisms." In ASME 1987 Design Technology Conferences. American Society of Mechanical Engineers, 1987. http://dx.doi.org/10.1115/detc1987-0023.

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Abstract A novel integrated technique permitting the simultaneous optimization of kinematic and dynamic characteristics in the synthesis of spatial mechanisms is shown. The nonlinear programming formulation determines mechanism variables which simultaneously minimize the maximum values of bearing reactions, joint torques, driving torque, shaking moment, and shaking force while constraining the maximum kinematic structural error to a prescribed bound. The method is applied to the design of a path generating RRSS spatial mechanism with prescribed input link timing. Dynamic reactions in the mecha
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Rhein, Sonke, and Knut Graichen. "Dynamic optimization of induction heat-up and surface hardening processes on complex spatial domains." In 2015 IEEE Conference on Control Applications (CCA). IEEE, 2015. http://dx.doi.org/10.1109/cca.2015.7320875.

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Ouyang, P. R., and Steven Cargnello. "Design and Optimization of a Spatial Hybrid Motion System." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28186.

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In this paper, a spatial hybrid motion system is developed that integrates two types of motions through one compliant mechanism: a macro motion driven by a DC servomotor and a micro motion driven by a PZT actuator. A unique feature of the developed hybrid motion system is the elimination of interaction between the macro motion and micro motion. Three issues are addressed in this study: (1) the design principle and implementation of the hybrid motion system; (2) the kinematic analysis and dynamic analysis; and (3) the optimization design of the hybrid motion system. For the micro motion, the fi
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Khandekar, Rahul M., and Vladimir V. Nikulin. "Mitigation of dynamic wavefront distortions using a nematic liquid crystal spatial light modulator and simplex optimization." In Lasers and Applications in Science and Engineering, edited by G. Stephen Mecherle. SPIE, 2006. http://dx.doi.org/10.1117/12.644931.

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Duffy, Joseph, and Carl D. Crane. "A Spatial Dynamic Analysis of an Excavator to Determine Bucket/Load Weight." In ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/mech-14186.

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Abstract This is essentially a report of the final phase of a major study undertaken for the Caterpillar Technical Center, Peoria, Illinois to determine to a high degree of accuracy the bucket/load weight of an excavator under dynamic conditions. It was quite remarkable that a relatively simple solution was obtained using a least squares approach (as opposed to using a highly non-linear optimization method) considering that there are a total of nine unknown moments and cross moments of inertia of the bucket/load together with the unknown location of the center of mass and the bucket/load weigh
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Reports on the topic "Spatial-Dynamic Optimization"

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Cai, Yongxia, Christopher M. Wade, Justin S. Baker, et al. Implications of alternative land conversion cost specifications on projected afforestation potential in the United States. RTI Press, 2018. http://dx.doi.org/10.3768/rtipress.2018.op.0057.1811.

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The Forestry and Agriculture Sector Optimization Model with Greenhouse Gases (FASOMGHG) has historically relied on regional average costs of land conversion to simulate land use change across cropland, pasture, rangeland, and forestry. This assumption limits the accuracy of the land conversion estimates by not recognizing spatial heterogeneity in land quality and conversion costs. Using data from Nielsen et al. (2014), we obtained the afforestation cost per county, then estimated nonparametric regional marginal cost functions for land converting land to forestry. These afforestation costs were
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