scholarly journals Recorded and potential alien invertebrate pests in Finnish agriculture and horticulture

2008 ◽  
Vol 20 (1) ◽  
pp. 96 ◽  
Author(s):  
I. VÄNNINEN ◽  
S. WORNER ◽  
E. HUUSELA-VEISTOLA
Keyword(s):  
Expert Knowledge ◽  
Pest Species ◽  
Self Organizing Map ◽  
Invasive Pests ◽  
Knowledge Based ◽  
Ornamental Tree ◽  
Exotic Pests ◽  
Potential Pest ◽  
Local Expert ◽  
Invertebrate Pests

It is assumed that climate change will promote pest invasions and their establishment in new regions. We have updated the list of current alien invertebrate pest species in Finland and produced a list of potential new alien pests using a self-organizing map (SOM) that ranks species in terms of their risk of entry into Finland. The 76 pest species recorded included 66 insects, 5 nematodes, 2 mites and 3 slugs. Nearly half of the alien species appeared to have invaded Finland during the last 48 years. The SOM analysis is considered a viable tool for identification of potentially high-risk invasive pests from among the multitude of potential alien invaders, and represents a useful complement to local expert knowledge-based risk assessment of potentially invasive pests. Along with the comparisons with databases of current and potential pest species, SOM analysis suggests that in the changing climate, the habitats at greatest risk from exotic pests in Finland are horticultural: orchards, ornamental hardy-nursery stocks, landscape and ornamental tree nurseries, and greenhouses.

Survey of the State-of-the-Art Expert/Knowledge Based Systems in Civil Engineering.

1986 ◽  
Author(s):  
Simon S. Kim ◽  
Mary Lou Maher ◽  
Raymond E. Levitt ◽  
Martin F. Rooney ◽  
Thomas J. Siller
Keyword(s):  
Civil Engineering ◽  
Expert Knowledge ◽  
State Of The Art ◽  
The State ◽  
Knowledge Based Systems ◽  
Knowledge Based

scholarly journals Experts versus Algorithms? Optimized Fuzzy Logic Energy Management of Autonomous PV Hybrid Systems with Battery and H2 Storage

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1777
Author(s):  
Lisa Gerlach ◽  
Thilo Bocklisch
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Fuzzy Logic Controller ◽  
Expert Knowledge ◽  
Large Power ◽  
Hybrid Energy ◽  
Knowledge Based ◽  
Long Term Storage ◽  
Fuzzy Logic Approach

Off-grid applications based on intermittent solar power benefit greatly from hybrid energy storage systems consisting of a battery short-term and a hydrogen long-term storage path. An intelligent energy management is required to balance short-, intermediate- and long-term fluctuations in electricity demand and supply, while maximizing system efficiency and minimizing component stress. An energy management was developed that combines the benefits of an expert-knowledge based fuzzy logic approach with a metaheuristic particle swarm optimization. Unlike in most existing work, interpretability of the optimized fuzzy logic controller is maintained, allowing the expert to evaluate and adjust it if deemed necessary. The energy management was tested with 65 1-year household load datasets. It was shown that the expert tuned controller is more robust to changes in load pattern then the optimized controller. However, simple readjustments restore robustness, while largely retaining the benefits achieved through optimization. Nevertheless, it was demonstrated that there is no one-size-fits-all tuning. Especially, large power peaks on the demand-side require overly conservative tunings. This is not desirable in situations where such peaks can be avoided through other means.

Heuristic Design of a Material Processing Component

1990 ◽  
Author(s):  
Vikram R. Jamalabad ◽  
Noshir A. Langrana ◽  
Yogesh Jaluria
Keyword(s):  
Heuristic Search ◽  
Expert Knowledge ◽  
Object Oriented ◽  
Engineering Process ◽  
Efficient Design ◽  
Cross Sectional ◽  
Design Algorithm ◽  
Initial Design ◽  
Knowledge Based ◽  
Processing Component

Abstract The main thrust of this research is in developing a knowledge-based system for the design of a mechanical engineering process. The study concentrates on developing methodologies for initial design and redesign in a qualitative format. The component selected is a die for plastic extrusion. A design algorithm using best first heuristic search and expert knowledge, both in procedural and declarative form, forms the core of the process. Initial design and redesign methodologies are presented that can enable efficient design of a component using expert knowledge. Some generality has been accomplished by the implementation of the techniques to dies of different cross sectional shapes. The software is written in Lisp within an object oriented software package using analysis modules written in C.

Knowledge-Based Design of Artificial Neural Network Topology for Additive Manufacturing Process Modeling: A New Approach and Case Study for Fused Deposition Modeling

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Hari P. N. Nagarajan ◽  
Hossein Mokhtarian ◽  
Hesam Jafarian ◽  
Saoussen Dimassi ◽  
Shahriar Bakrani-Balani ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Expert Knowledge ◽  
Fused Deposition ◽  
Knowledge Based ◽  
Deposition Modeling ◽  
Artificial Neural

Additive manufacturing (AM) continues to rise in popularity due to its various advantages over traditional manufacturing processes. AM interests industry, but achieving repeatable production quality remains problematic for many AM technologies. Thus, modeling different process variables in AM using machine learning can be highly beneficial in creating useful knowledge of the process. Such developed artificial neural network (ANN) models would aid designers and manufacturers to make informed decisions about their products and processes. However, it is challenging to define an appropriate ANN topology that captures the AM system behavior. Toward that goal, an approach combining dimensional analysis conceptual modeling (DACM) and classical ANNs is proposed to create a new type of knowledge-based ANN (KB-ANN). This approach integrates existing literature and expert knowledge of the AM process to define a topology for the KB-ANN model. The proposed KB-ANN is a hybrid learning network that encompasses topological zones derived from knowledge of the process and other zones where missing knowledge is modeled using classical ANNs. The usefulness of the method is demonstrated using a case study to model wall thickness, part height, and total part mass in a fused deposition modeling (FDM) process. The KB-ANN-based model for FDM has the same performance with better generalization capabilities using fewer weights trained, when compared to a classical ANN.

scholarly journals Enhancing ecosystem restoration efficiency through spatial and temporal coordination

2015 ◽  
Vol 112 (19) ◽  
pp. 6236-6241 ◽  
Author(s):  
Thomas M. Neeson ◽  
Michael C. Ferris ◽  
Matthew W. Diebel ◽  
Patrick J. Doran ◽  
Jesse R. O’Hanley ◽  
...  
Keyword(s):  
Great Lakes ◽  
Large Scale ◽  
Expert Knowledge ◽  
Spatial Scales ◽  
Small Scale ◽  
Space And Time ◽  
Ecosystem Connectivity ◽  
Breeding Grounds ◽  
Local Expert ◽  
Conservation Projects

In many large ecosystems, conservation projects are selected by a diverse set of actors operating independently at spatial scales ranging from local to international. Although small-scale decision making can leverage local expert knowledge, it also may be an inefficient means of achieving large-scale objectives if piecemeal efforts are poorly coordinated. Here, we assess the value of coordinating efforts in both space and time to maximize the restoration of aquatic ecosystem connectivity. Habitat fragmentation is a leading driver of declining biodiversity and ecosystem services in rivers worldwide, and we simultaneously evaluate optimal barrier removal strategies for 661 tributary rivers of the Laurentian Great Lakes, which are fragmented by at least 6,692 dams and 232,068 road crossings. We find that coordinating barrier removals across the entire basin is nine times more efficient at reconnecting fish to headwater breeding grounds than optimizing independently for each watershed. Similarly, a one-time pulse of restoration investment is up to 10 times more efficient than annual allocations totaling the same amount. Despite widespread emphasis on dams as key barriers in river networks, improving road culvert passability is also essential for efficiently restoring connectivity to the Great Lakes. Our results highlight the dramatic economic and ecological advantages of coordinating efforts in both space and time during restoration of large ecosystems.

Expert Knowledge-Based Traction Control of a Truck Using Fuzzy Logic

1996 ◽  
Vol 29 (1) ◽  
pp. 7867-7872
Author(s):  
Ka C. Cheok ◽  
Kazuyuki Kobayashi ◽  
Francis B. Hoogterp
Keyword(s):  
Fuzzy Logic ◽  
Expert Knowledge ◽  
Traction Control ◽  
Knowledge Based

scholarly journals Towards a reasoned 1D river model calibration

2005 ◽  
Vol 7 (2) ◽  
pp. 91-104 ◽  
Author(s):  
Jean-Philippe Vidal ◽  
Sabine Moisan ◽  
Jean-Baptiste Faure ◽  
Denis Dartus
Keyword(s):  
Model Calibration ◽  
Expert Knowledge ◽  
Fixed Bed ◽  
Rainfall Runoff ◽  
Simulation Code ◽  
Hydraulic Simulation ◽  
Flow Equations ◽  
Knowledge Based ◽  
River Hydraulics ◽  
Knowledge Levels

Model calibration remains a critical step in numerical modelling. After many attempts to automate this task in water-related domains, questions about the actual need for calibrating physics-based models are still open. This paper proposes a framework for good model calibration practice for end-users of 1D hydraulic simulation codes. This framework includes a formalisation of objects used in 1D river hydraulics along with a generic conceptual description of the model calibration process. It was implemented within a knowledge-based system integrating a simulation code and expert knowledge about model calibration. A prototype calibration support system was then built up with a specific simulation code solving subcritical unsteady flow equations for fixed-bed rivers. The framework for model calibration is composed of three independent levels related, respectively, to the generic task, to the application domain and to the simulation code itself. The first two knowledge levels can thus easily be reused to build calibration support systems for other application domains, like 2D hydrodynamics or physics-based rainfall–runoff modelling.

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