Relevant bibliographies by topics / Knowledge-based planning

Contents

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

Academic literature on the topic 'Knowledge-based planning'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

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Journal articles on the topic "Knowledge-based planning"

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Melis, Erica, and Jörg Siekmann. "Knowledge-based proof planning." Artificial Intelligence 115, no. 1 (November 1999): 65–105. http://dx.doi.org/10.1016/s0004-3702(99)00076-4.

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Lee, Huaming, Jon Sims Williams, and James Tannock. "Knowledge-based inspection planning." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 6, no. 3 (August 1992): 149–62. http://dx.doi.org/10.1017/s0890060400003048.

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Inspection planning is a process of reasoning about inspection activities. As a result, a sequence of inspection actions is formulated, which, when performed, will achieve the desired measurements. In manufacturing, automated inspection technologies, such as Computer-Aided Inspection (CAI) or Co-ordinate Measuring Machines (CMMs), will be facilitated by inspection planning. Inspection planning involves the following four aspects: representation of inspection features; process formalization; modeling of inspection activities; and, finally, plan synthesis. This paper discusses an approach to knowledge-based inspection planning. Accordingly, a prototype inspection planning system has been developed, which is also described in this paper.
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Morad, Ayman A., and Yvan J. Beliveau. "Knowledge‐Based Planning System." Journal of Construction Engineering and Management 117, no. 1 (March 1991): 1–12. http://dx.doi.org/10.1061/(asce)0733-9364(1991)117:1(1).

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Bardens, Rupert, and Dimitris Karagiannis. "Knowledge-based manpower planning." Annals of Operations Research 16, no. 1 (December 1988): 347–74. http://dx.doi.org/10.1007/bf02283753.

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Hung, Wai Man, Nelson T. C. Fung, Amy T. Y. Chang, Michael C. H. Lee, and Wai Tong Ng. "Knowledge-based planning in nasopharyngeal carcinoma." Annals of Nasopharynx Cancer 4 (August 2020): 6. http://dx.doi.org/10.21037/anpc-20-12.

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Aarts, R. J. "Knowledge-based Planning of Mashing Profiles." IFAC Proceedings Volumes 25, no. 2 (March 1992): 387–90. http://dx.doi.org/10.1016/s1474-6670(17)50398-5.

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YANG, Y., and L. XING. "Clinical knowledge-based inverse treatment planning." International Journal of Radiation OncologyBiologyPhysics 60 (September 2004): S624. http://dx.doi.org/10.1016/s0360-3016(04)01941-8.

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Cross, George R., Mitchell A. Potter, J. Douglass Whitehead, and James T. Smith. "Knowledge-based TDRSS momentum unload planning." Telematics and Informatics 8, no. 4 (January 1991): 253–65. http://dx.doi.org/10.1016/s0736-5853(05)80052-8.

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Yang, Yong, and Lei Xing. "Clinical knowledge-based inverse treatment planning." Physics in Medicine and Biology 49, no. 22 (October 25, 2004): 5101–17. http://dx.doi.org/10.1088/0031-9155/49/22/006.

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Tenma, Tadashi, and Kichizoo Akashi. "Knowledge Based Packing Layout Planning Method." IEEJ Transactions on Electronics, Information and Systems 107, no. 2 (1987): 165–72. http://dx.doi.org/10.1541/ieejeiss1987.107.2_165.

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Dissertations / Theses on the topic "Knowledge-based planning"

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Grant, Timothy John. "Inductive learning of knowledge-based planning operators." [Maastricht : Maastricht : Rijksuniversiteit Limburg] ; University Library, Maastricht University [Host], 1996. http://arno.unimaas.nl/show.cgi?fid=6686.

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Tang, Xiaoqing. "Knowledge based inspection planning system for rotational components." Thesis, University of Manchester, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.243932.

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Scholz, Volker. "Knowledge-based locomotive planning for the Swedish railway." [S.l.] : Universität Stuttgart , Fakultät Informatik, 1998. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB7400642.

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Liang, Qixiong. "An intelligent strategy planning tool for decision support." Thesis, Queen's University Belfast, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.300611.

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Diab, Mohammed. "Knowledge representation and reasoning for perception-based manipulation planning." Doctoral thesis, Universitat Politècnica de Catalunya, 2021. http://hdl.handle.net/10803/671505.

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This thesis develops a series of modeling and reasoning tools for knowledge-oriented manipulation planning in semi/unstructured environments. The main idea is to use high-level knowledge-based reasoning to capture a rich semantic description of the scene, knowledge about the physical behavior of the objects, and inference mechanism to reason about the potential manipulation actions. Moreover, a multi-model sensory module is proposed to perceive the objects in the environment and build the ontological knowledge. The first part of the thesis is focused on the techniques to provide useful knowledge to guide and facilitate the planning process within a classical-based manipulation planning framework. This planning framework facilitates the combination of task and motion planning approaches which includes Fast Forward (FF), a classical symbolic planning approach to compute the sequence of actions to be done in a certain task, and physics-based motion planning which deals with motions and possible interactions with the objects. The tool proposed to provide useful knowledge to the planning process is called Perception and Manipulation Knowledge (PMK). It provides, on the one hand, a standardized formalization under several foundations, such as the Suggested Upper Merged Ontology (SUMO), and the Core Ontology for Robotics and Automation (CORA), in order to facilitate the shareability and reusability when the interaction between humans and/or robots is done. On the other hand, it provides the inference mechanism to reason about TAMP requirements, such as robot capabilities, action constraints, action feasibility, and manipulation behaviors. Moreover, PMK allows breaking the closed-world assumption of classical-based manipulation planning approaches. This proposal has been tested for a serving task in a table-top manipulation problem.
Esta tesis desarrolla una serie de herramientas de modelado y razonamiento para la planificación de la manipulación basada en el conocimiento en entornos no estructurados o semiestructurados. La idea principal es utilizar un razonamiento basado en el conocimiento de alto nivel para capturar una descripción semántica de la escena, conocimiento sobre el comportamiento físico de los objetos y un mecanismo de inferencia para razonar sobre las posibles acciones de manipulación. Además, se propone un módulo sensorial multimodelo para percibir los objetos del entorno y construir conocimiento ontológico. La primera parte de la tesis se centra en las técnicas para proporcionar conocimientos útiles para guiar y facilitar el proceso de planificación dentro de un marco de planificación de manipulación clásico. Este marco de planificación facilita la combinación de enfoques de planificación de tareas y movimientos (TAMP) que incluye Fast Forward (FF) que es un enfoque clásico de planificación simbólica para calcular la secuencia de acciones a realizar en una determinada tarea, y la planificación de movimiento basada en la física que trata con movimientos y posibles interacciones con los objetos. La herramienta propuesta para aportar conocimientos útiles al proceso de planificación se denomina Conocimiento de Percepción y Manipulación (PMK), la cual proporciona una formalización estandarizada bajo varios fundamentos, como la Ontología Superior Sugerida Sugerida (SUMO), y la Ontología Core para Robótica y Automatización (CORA), con el fin de facilitar la compartibilidad y reutilización cuando se produzca la interacción entre humanos y/o robots. La segunda parte de la tesis se centra en proporcionar conocimientos útiles para un enfoque de planificación basado en la lógica. Está particularizado para el ensamblaje, que tiene en cuenta lacciones de manipulación para acoplar/desacoplar o unir/separar objetos. Las secuencias de ensamblaje se pueden representar de forma elegante usando teorías de lógica descriptiva. Con tal secuencia, el robot puede descubrir el próximo paso en el ensamblaje a través de la inferencia lógica. Sin embargo, antes de realizar una acción, el robot debe asegurarse de que se cumplan varias restricciones espaciales, como que las partes que se van a unir sean accesibles, no ocluidas, etc. Tales inferencias son muy complicadas de respaldar en teorías lógicas, pero existen algoritmos especializados que calculan de manera eficiente relaciones cualitativas, como si un objeto es accesible. Aquí se propone un razonamiento heterogéneo que requiere la integración entre el nivel de planificación de ensamblajes basado en el conocimiento y el nivel geométrico, que incluye módulos para inferir sobre las relaciones espaciales y la viabilidad de las acciones. La tercera parte de la tesis se centra en el uso de la experiencia basada en el conocimiento, llamado conocimiento experiencial, en problemas de manipulación cotidianos, como por ejemplo, en aplicaciones de robótica de servicios, como servir una taza en un entorno desordenado, donde suelen encontrarse algunas habilidades repetibles como recoger, dejar o navegar. Para manejar de manera eficiente estas tareas, en lugar de planificarlas por completo cada vez (lo que podría ser computacionalmente costoso), se propone la integración de módulos para adaptar esas habilidades en diferentes situaciones. En este sentido, se presenta un marco de planificación y ejecución para tareas de manipulación robótica, el cual se equipa de un módulo con conocimiento experiencial (aprendido de su experiencia o dado por el usuario) sobre cómo ejecutar un conjunto de habilidades, tales como recoger, dejar, navegar o abrir un cajón, utilizando flujos de trabajo y trayectorias de robots.
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蕭世良 and Sai-leung Siu. "A knowledge based process planning system for prismatic parts." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1991. http://hub.hku.hk/bib/B31232784.

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Formoso, Carlos Torres. "A knowledge based framework for planning house building projects." Thesis, University of Salford, 1991. http://usir.salford.ac.uk/14738/.

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This thesis describes the development of a knowledge based system which encapsulates some of the expertise used by a number of experienced construction planners for planning the construction stage of low rise house building projects in the U.K. The general objective of the research was to investigate the feasibility of using knowledge engineering for developing models of construction planning expertise, which could be employed for tackling some of the existing knowledge bottlenecks in the construction industry. The resulting system can be described as a knowledge based framework designed for supporting the decision making process involved in planning house building at a tactical level. One of the main features of this framework is its ability to cope with incomplete information. The knowledge acquisition process involved both the elicitation of knowledge directly from experts, and the analysis of construction plans from several past housing developments. The model was implemented on an expert system shell called LEONARDO Level 3, which runs in any standard IBM-PC micro-computer or compatibles. The evaluation of the system focused on the validity of the model, i.e. the degree at which the outcomes of the system resembled the outcomes of the human expertise being modelled in the knowledge base. A prescriptive method of validation was devised specifically for this study, involving both experts that had provided expertise for the system, and external experts.
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Hooper, Jonathan Nigel. "A knowledge based system for strategic sludge disposal planning." Thesis, Cardiff University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262163.

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Kumar, Dipmani. "A knowledge based system for irrigation planning in Virginia." Thesis, Virginia Tech, 1990. http://hdl.handle.net/10919/31650.

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Problems associated with irrigation in humid regions include uncertainty of whether irrigation will be necessary in a given year, and the question of whether crop response will be sufficient to make the required investment profitable in the long run. A prototype knowledge based system (KBS) has been developed to determine the economic feasibility of a range of irrigation systems for site specific conditions. The KBS uses information input by the user to determine possible irrigation alternatives and provides an economic evaluation of suitable systems based on domain-specific knowledge about soils, crops, irrigation costs, and agricultural drought in Virginia. Irrigation systems considered by the KBS include center-pivot, traveling gun and portable pipe systems. Crops considered are field corn, soybeans, and peanuts. Preliminary evaluation showed that the KBS was able to effectively determine if portable pipe, traveling gun and center pivot irrigation systems were suitable, and provide an economic evaluation of these systems for site specific situations in Virginia. The KBS developed in this study provides a basic framework which can be used to build a more comprehensive system which would address a larger domain, considering additional systems and crops.
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Klaasen, I. T. "Knowledge-based design developing urban & regional design into a science /." Delft : Delft University Press, 2004. http://www.ebrary.com/.

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Books on the topic "Knowledge-based planning"

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Mockler, Robert J. Knowledge-based systems for strategic planning. Englewood Cliffs, N.J: Prentice Hall, 1989.

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Tate, Austin. A review of knowledge-based planning techniques. Edinburgh: Artificial Intelligence Applications Institute, University of Edinburgh, 1985.

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Chris, Hendrickson, and Rehak Daniel R, eds. Knowledge-based process planning for construction and manufacturing. Boston: Academic Press, 1989.

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Mockler, Robert J. Knowledge-based systems for management decisions. Englewood Cliffs, N.J: Prentice Hall, 1989.

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Science Council of British Columbia. Strategic Planning for Applied Research and Knowledge. Fiscal Committee. Financing a knowledge based future: Final report. [Brtish Columbia]: Science Council of British Columbia, 1992.

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Innovation networks in knowledge-based firms: Developing ICT-based integrative competences. Cheltenham, UK: Edward Elgar, 2009.

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Shaw, Michael. A knowledge-based approach to flexible planning and scheduling. [Urbana, Ill.]: University of Illinois at Urbana-Champaign, College of Commerce and Business Administration, 1985.

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Formoso, Carlos Torres. A knowledge based framework for planning house building projects. Salford: University of Salford, 1991.

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Shaw, Michael. Incorporating machine learning in knowledge-based process planning systems: An explanation-based approach. [Urbana, Ill.]: College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1990.

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K, Wensley Anthony, ed. CAPEX: A knowledge-based expert system for substantive audit planning. Princeton, N.J: M. Wiener Publishers, 1996.

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Book chapters on the topic "Knowledge-based planning"

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Muñoz-Avila, Héctor, Kalyan Gupta, David W. Aha, and Dana Nau. "Knowledge-Based Project Planning." In Knowledge Management and Organizational Memories, 125–34. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0947-9_11.

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El Naqa, Issam. "Knowledge-Based Treatment Planning." In Machine Learning in Radiation Oncology, 193–99. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18305-3_10.

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Metaxiotis, Kostas, Dimitris Askounis, and John Psarras. "Expert Systems Technology in Production Planning and Scheduling." In Intelligent Knowledge-Based Systems, 797–817. Boston, MA: Springer US, 2005. http://dx.doi.org/10.1007/978-1-4020-7829-3_23.

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Howe, Adele E., Anneliese von Mayrhauser, and Richard T. Mraz. "Test Case Generation as an AI Planning Problem." In Knowledge-Based Software Engineering, 77–106. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-0-585-34714-1_5.

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Schmoldt, Daniel L., and H. Michael Rauscher. "Planning the Application." In Building Knowledge-Based Systems for Natural Resource Management, 104–38. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1155-3_4.

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Zalaket, Joseph, and Guy Camilleri. "State-Based Planning with Numerical Knowledge." In Lecture Notes in Computer Science, 53–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45224-9_11.

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Ito, Y., and H. Shinno. "Knowledge-Based Computer-Aided Process Planning." In Artificial Intelligence in Design, 273–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-74354-2_11.

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Adelman, Leonard, and Sharon L. Riedel. "Planning and Managing Knowledge-Based System Evaluations." In Handbook for Evaluating Knowledge-Based Systems, 307–39. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6171-2_9.

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Chang, Kai-Hsiung, and William G. Wee. "A Knowledge-Based Mechanical Assembly Planning System." In Expert Systems in Engineering Applications, 291–306. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-84048-7_15.

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Duchessi, Peter, and Robert M. O’Keefe. "A Knowledge-based Approach to Production Planning." In Artificial Intelligence in Operational Research, 151–64. London: Macmillan Education UK, 1992. http://dx.doi.org/10.1007/978-1-349-12362-9_16.

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Conference papers on the topic "Knowledge-based planning"

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Delchambre, Alain, David Coupez, and Pierre Gaspart. "Knowledge Based Process Planning In Robotized Assembly." In SPIE 1989 Technical Symposium on Aerospace Sensing, edited by Mohan M. Trivedi. SPIE, 1989. http://dx.doi.org/10.1117/12.969325.

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Haton. "Knowledge-based Decision Making For Radiotherapy Planning." In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.594648.

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Haton, Marie-Christine. "Knowledge-based decision making for radiotherapy planning." In 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.5761306.

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Gilmore, John F., Antonio C. Semeco, and Pipat Eamsherangkoon. "Knowledge-Based Route Planning Through Natural Terrain." In 1985 Technical Symposium East, edited by John F. Gilmore. SPIE, 1985. http://dx.doi.org/10.1117/12.948415.

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Winstanley, G. "A planning system for large-scale industrial projects." In IEE Colloquium on `Knowledge-Based Approaches to Automation in Construction'. IEE, 1995. http://dx.doi.org/10.1049/ic:19950835.

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Taleshian, Tahereh, and Sara Minagar. "Motion planning for an autonomous underwater vehicle." In 2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI). IEEE, 2015. http://dx.doi.org/10.1109/kbei.2015.7436061.

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Bracanović, Slobodan. "THE PLANNING PROCESS AS A MODERN FORM OF DIRECTING PROFITABLE BUSINESS ACTIVITIES AND CONSCIOUS COORDINATION." In 6th International Scientific Conference ERAZ - Knowledge Based Sustainable Development. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2020. http://dx.doi.org/10.31410/eraz.2020.139.

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Planning was reaffirmed after the collapse of the neoliberal economic doctrine (at the beginning of this century). The relations between the plan and the market are complementary and non-exclusive. The market is also planned and market spontaneity is suppressed. The planning of all the levels is primarily present in the Eurasian economies that are not in crisis. The plan is also a creativity space.
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Wang, Fengyu, Tayjin Chua, William Liu, and Tianxiang Cai. "Knowledge-based Multi-site Capacity Planning using Agents." In 2006 IEEE International Conference on Industrial Informatics. IEEE, 2006. http://dx.doi.org/10.1109/indin.2006.275608.

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Gilmore, John F., D. Lamont Williams, and Sheila Thornton. "A Knowledge-Based Approach To Planning And Scheduling." In SPIE 1989 Technical Symposium on Aerospace Sensing, edited by Mohan M. Trivedi. SPIE, 1989. http://dx.doi.org/10.1117/12.969341.

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Zhang, Linda, Qianli Xu, and Yongyi Shou. "Planning process families with a knowledge-based system." In 2011 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2011. http://dx.doi.org/10.1109/ieem.2011.6118229.

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Reports on the topic "Knowledge-based planning"

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McDermott, Drew, and Gregory Hager. Knowledge-Based Planning. Fort Belvoir, VA: Defense Technical Information Center, September 1992. http://dx.doi.org/10.21236/ada257209.

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McDermott, Drew, and Gregory Hager. Knowledge-Based Planning. Fort Belvoir, VA: Defense Technical Information Center, September 1993. http://dx.doi.org/10.21236/ada279697.

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Day, William B. Constraints Logic Programming in Knowledge-Based Planning Domains. Fort Belvoir, VA: Defense Technical Information Center, December 1992. http://dx.doi.org/10.21236/ada262958.

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Fox, Mark S., and Katia P. Sycara. Knowledge-Based Logistics Planning and Its Application in Manufacturing and Strategic Planning. Fort Belvoir, VA: Defense Technical Information Center, January 1990. http://dx.doi.org/10.21236/ada219928.

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Swartout, William R., and Yolanda Gil. EXPECT: A User-Centered Environment for the Development and Adaptation of Knowledge-Based Planning Aids. Fort Belvoir, VA: Defense Technical Information Center, January 1996. http://dx.doi.org/10.21236/ada459766.

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Bridges, Todd, Jeffrey King, Jonathan Simm, Michael Beck, Georganna Collins, Quirjin Lodder, and Ram Mohan. Overview : International Guidelines on Natural and Nature-Based Features for Flood Risk Management. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41945.

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The application of natural and nature‑based features (NNBF) has grown steadily over the past 20 years, supported by calls for innovation in flood risk management (FRM) and nature‑based solutions from many different perspectives and organizations. Technical advancements in support of NNBF are increasingly the subject of peer‑reviewed and other technical literature. A variety of guidance has been published by numerous organizations to inform program‑level action and technical practice for specific types of nature‑based solutions. This effort to develop international guidelines on the use of NNBF was motivated by the need for a comprehensive guide that draws directly on the growing body of knowledge and experience from around the world to inform the process of conceptualizing, planning, designing, engineering, constructing, and operating NNBF.
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Phuong, Vu Tan, Nguyen Van Truong, and Do Trong Hoan. Commune-level institutional arrangements and monitoring framework for integrated tree-based landscape management. World Agroforestry, 2021. http://dx.doi.org/10.5716/wp21024.pdf.

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Governance is a difficult task in the context of achieving landscape multifunctionality owing to the multiplicity of stakeholders, institutions, scale and ecosystem services: the ‘many-multiple’ (Cockburn et al 2018). Governing and managing the physical landscape and the actors in the landscape requires intensive knowledge and good planning systems. Land-use planning is a powerful instrument in landscape governance because it directly guides how actors will intervene in the physical landscape (land use) to gain commonly desired value. It is essential for sustaining rural landscapes and improving the livelihoods of rural communities (Bourgoin and Castella 2011, Bourgoin et al 2012, Rydin 1998), ensuring landscape multifunctionality (Nelson et al 2009, Reyers et al 2012) and enhancing efficiency in carbon sequestration, in particular (Bourgoin et al 2013, Cathcart et al 2007). It is also considered critical to the successful implementation of land-based climate mitigation, such as under Nationally Determined Contributions (NDCs), because the Land Use, Land-Use Change and Forestry (LULUCF) sector is included in the mitigation contributions of nearly 90 percent of countries in Sub-Saharan and Southern Asia countries and in the Latin American and Caribbean regions (FAO 2016). Viet Nam has been implementing its NDC, which includes forestry and land-based mitigation options under the LULUCF sector. The contribution of the sector to committed national emission reduction is significant and cost-effective compared with other sectors. In addition to achieving emission reduction targets, implementation of forestry and land-based mitigation options has the highest benefits for social-economic development and achieving the Sustainable Development Goals (MONRE 2020). Challenges, however, lie in the way national priorities and targets are translated into sub-national delivery plans and the way sub-national actors are brought together in orchestration (Hsu et al 2019) in a context where the legal framework for climate-change mitigation is elaborated at national rather than sub-national levels and coordination between government bodies and among stakeholders is generally ineffective (UNDP 2018). In many developing countries, conventional ‘top–down’, centralized land-use planning approaches have been widely practised, with very little success, a result of a lack of flexibility in adapting local peculiarities (Amler et al 1999, Ducourtieux et al 2005, Kauzeni et al 1993). In forest–agriculture mosaic landscapes, the fundamental question is how land-use planning can best conserve forest and agricultural land, both as sources of economic income and environmental services (O’Farrell and Anderson 2010). This paper provides guidance on monitoring integrated tree-based landscape management at commune level, based on the current legal framework related to natural resource management (land and forest) and the requirements of national green-growth development and assessment of land uses in two communes in Dien Bien and Son La provinces. The concept of integrated tree based landscape management in Viet Nam is still new and should be further developed for wider application across levels.
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Zachry, Anne. Bridging the Gap Between Academia and Practice: Possibilities for Research Collaboration and Funding. University of Tennessee Health Science Center, 2019. http://dx.doi.org/10.21007/chp.ot.fp.2019.0002.

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Abstract:
Preparing a successful small grant proposal involves research, planning, preparation, and determination, but obtaining funding for a creative project is not unrealistic. Practitioners are in the trenches on a daily basis, and many likely have novel ideas and relevant questions, especially when it comes to interventions. These intervention questions are important, with the American Occupational Therapy Association reporting that more studies are needed to investigate and support occupation-based intervention. By developing partnerships, educators, practitioners, and students can engage in small scale projects to further the knowledge base in the field of occupational therapy.
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9

Determining an effective and replicable communication-based mechanisms for improving young couples' access to and use of reproductive health information and services in Nepal—An operations research study. Population Council, 2004. http://dx.doi.org/10.31899/rh17.1009.

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This operations research study sought to determine an effective communication-based model for increasing the involvement of community-based groups in improving access to and use of reproductive health services and information by young married couples. The study employed a quasi-experimental design with two experimental and two nonequivalent control groups in the Udaypur district of Nepal. As stated in this report, this OR study clearly demonstrates the effectiveness of communication-based models such as the formation and reactivation of Youth Communication Action Groups and Mother’s groups, basic and refresher training, group interaction and mobilization, and social events in creating an enabling environment for young married couples to learn and interact about sexual and reproductive health issues. The increase in reproductive health-related knowledge and practice among young married women has been high in both experimental areas. However, changes in the practice of family planning and antenatal care have not shown consistent trends probably because of the conflict situation in the project sites during the implementation phase.
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