Hiep Xuan Huynh

On weather affecting to brown plant hopper invasion using an agent-based model

In this paper, a new agent-based model is proposed to model and simulate visually growth and invasion of brown plant hoppers in different localities and at different times under effects of weather conditions such as temperature, humidity, rainfall and wind factors. The results from simulation are validated with light traps data collected in communes in the Mekong Delta region and show that brown plant hoppers life is affected by weather.

Modeling the brown plant hoppers surveillance network using agent-based model: application for the Mekong Delta region

This paper aims at modeling a brown plant hopper (BPH) surveillance network, called BPH surveillance network model (BSNM). In this model, we apply the Unit Disk Graph (UDG) technique to setup a graph with multiple surveillance nodes (light traps). An agent-based model (ABM) is built to model some necessary environmental and ecological factors, in which, the model contains two smaller models called the Environmental and Ecological Model (EEM) and the Surveillance Network Model (SNM). The key ideas of the surveillance network concentrate on the density estimations based on UDG technique and the up-scale aggregation via multiple levels of spatial regions. The simulation is applied for the province Dong Thap, a typical province in region of Mekong Delta of Vietnam.

Modeling a Surveillance Network Based on Unit Disk Graph Technique – Application for Monitoring the Invasion of Insects in Mekong Delta Region

This paper aims at introducing a novel general simulation model named Unit Disk Graph-based Surveillance Network Model (USNM) for an ecosystem. This model can be applied for multiple types of surveillance network, supported by two main techniques: (1)Unit Disk Graph and (2)clustering based on the correlation measures. USNM is a part of a bigger multi-agent system, where the observed objects can be implemented as a system dynamics. Three main agents of USNM are vertices, edges and graph/sub-graphs. Furthermore, we also introduce the Brown plant hopper Surveillance Network Model (BSNM), a concrete case of USNM. The simulation for BSNM is applied for three provinces of the Mekong Delta region, Vietnam.

Estimating the density of brown plant hoppers from a light-traps network based on unit disk graph

This paper is aimed at introducing a new approach to estimate the density of Brown Plant Hoppers (BPHs) at provincial scale. The model is based on the topology of a light-traps network (to gather the information about the BPHs) of a province. The BPHs density is determined based on Unit Disk Graph technique where each light-trap becomes a vertex and the edges reflect the relations on the mutual transfer of BPHs between light-traps. The model uses the historical light-traps data as the input to estimate the density of unknown location via an influence function. The experimental results of the model are performed in a typical province of the Mekong Delta region, namely Dong Thap province of Vietnam.

Upscaling and Assessing Information of Agriculture Indicators in Agent-Based Assessment Model from Field to Region Scale

Problems related to brown plant hopper outbreaks management in the Mekong Delta-Vietnam are complex and need aggregating information across administrative scales. Brown plant hopper density and environmental indicators are main factors that support stakeholders have suitable decision making. Due to detail levels of information are different from field scale to region scale, upscaling information is required, this paper aims at designing an agent-based assessment model and proposes an upscaling method to aggregate and assess information from field to region scales. A case study presents conveying rice area infested by brown plant hoppers across scales and results could help stakeholders assess damage levels caused by Brown plant hoppers in rice crop seasons.

Assessing rice area infested by brown plant hopper using agent-based and dynamically upscaling approach

This paper introduces an agent-based framework to modeling and simulate assessing rice area infested by brown plant hoppers from field to regional scales using agent-based and upscaling approach. Because detail levels of infestation rice area information are different from small scale to large scale, infestation rice area information are collected from fields in the Mekong Delta region-Vietnam and are upscaled to province scale, results are validated by province estimation reports. From the results, infestation rice area information can be used as an indicator for assessing damage levels of rice crop seasons caused by Brown plant hoppers, agent-based model and uscaling method could be an usefull tool for aggregating information from field to decision-makers and support planning argicultural strategics.

Finding the Most Interesting Association Rules by Aggregating Objective Interestingness Measures

Association rule post-processing is a research challenge in KDD. In this post-processing task, objective interestingness measures are very useful for finding interesting rules possessing certain characteristics. Till now, the usual method for using objective interestingness measures is to select one or several suitable measures for filtering rules. This paper proposes a new approach to aggregate a set of interestingness measures using the Choquet integral as an advanced aggregation operator. Since an objective interestingness measure is considered as a point of view on rule quality, the aggregation of a set of objective interestingness measures can extract rules satisfying many points of view. The experiment is carried out on different groups (i.e. different natures) of objective interestingness measures to observe their behaviors.

Spatial Estimator of Brown Plant Hopper Density from Light Traps Data

This paper aims to define an optimal interpolation technique to estimate the density of brown plant hopper (BPH) in Dongthap Province among the Mekong delta in Vietnam. The technique is chosen by assessment between the two methods: Inverse Distance Weight and Ordinary Kriging. First, sample data of light-traps are analyzed by the two mentioned methods running on R packages. Second, the results are visualized on the multi-agent system (GAMA) combined with the geographic information system (GIS). As a result, managers can easily survey the density of BPH populations on rice fields to control the damage of BPH more effectively and bring in higher yield for farmers.

An implementation of framework of business intelligence for agent-based simulation

Integrated environmental modeling approaches, especially agent-based modeling ones, are increasingly used in large-scale decision support systems. A major consequence of this trend is the manipulation and generation of a huge amount of data in simulations, which require to be efficiently managed. In this paper, we present a Combination Framework of Business intelligence solution and Multi-agent platform (CFBM) and its implementation on the GAMA platform. CFBM is a logical framework dedicated to the management of the input and output data of simulations, as well as the corresponding empirical datasets in an integrated way and the analysis on integrated data, which we propose as a coupling of two major methodologies: Multi-Agent Simulation (MAS) on one hand and Business Intelligence (BI) solution on the other. An integrated model of a surveillance network and Brown Plant Hopper (BPH) invasion is presented. This model is used throughout the paper as a case study of CFBM regarding to the database accesses, the integration of internal and external processing, and the model validation tasks. We show how the proposed combination framework can be an appropriate choice for all decision-support systems with a huge data, hence the modelers can be also encouraged to develop the big model in a large scale.

IoT Services for Solving Critical Problems in Vietnam: A Research Landscape and Directions

Critical problems in Vietnam - such as food safety, traffic management, saltwater intrusion, and wastewater management - require novel Internet of Things (IoT) solutions. Here, the authors analyze current research and developments and propose specific IoT services as solutions.