Parallel Decision Tree with Application to Water Quality Data Analysis

Abstract. Decision tree is a popular classification technique in many applications, such as retail target marketing, fraud detection and design of telecommunication service plans. With the information exploration, the existing classification algorithms are not good enough to tackle large data set. In order to deal with the problem, many researchers try to design efficient parallel classification algorithms. Based on the current and powerful parallel programming framework -MapReduce, we propose a parallel ID3 classification algorithm(PID3 for short). We use water quality data monitoring the Changjiang River which contains 17 branches as experimental data. As the data are time series, we process the data to attribute data before using the decision tree. The experimental results demonstrate that the proposed algorithm can scale well and efficiently process large datasets on commodity hardware

GPU-accelerated stochastic predictive control of drinking water networks

Despite the proven advantages of scenario-based stochastic model predictive control for the operational control of water networks, its applicability is limited by its considerable computational footprint. In this paper we fully exploit the structure of these problems and solve them using a proximal gradient algorithm parallelizing the involved operations. The proposed methodology is applied and validated on a case study: the water network of the city of Barcelona.Comment: 11 pages in double column, 7 figure

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

An information adaptive system study report and development plan

The purpose of the information adaptive system (IAS) study was to determine how some selected Earth resource applications may be processed onboard a spacecraft and to provide a detailed preliminary IAS design for these applications. Detailed investigations of a number of applications were conducted with regard to IAS and three were selected for further analysis. Areas of future research and development include algorithmic specifications, system design specifications, and IAS recommended time lines

Simulating California reservoir operation using the classification and regression-tree algorithm combined with a shuffled cross-validation scheme

The controlled outflows from a reservoir or dam are highly dependent on the decisions made by the reservoir operators, instead of a natural hydrological process. Difference exists between the natural upstream inflows to reservoirs and the controlled outflows from reservoirs that supply the downstream users. With the decision maker's awareness of changing climate, reservoir management requires adaptable means to incorporate more information into decision making, such as water delivery requirement, environmental constraints, dry/wet conditions, etc. In this paper, a robust reservoir outflow simulation model is presented, which incorporates one of the well-developed data-mining models (Classification and Regression Tree) to predict the complicated human-controlled reservoir outflows and extract the reservoir operation patterns. A shuffled cross-validation approach is further implemented to improve CART's predictive performance. An application study of nine major reservoirs in California is carried out. Results produced by the enhanced CART, original CART, and random forest are compared with observation. The statistical measurements show that the enhanced CART and random forest overperform the CART control run in general, and the enhanced CART algorithm gives a better predictive performance over random forest in simulating the peak flows. The results also show that the proposed model is able to consistently and reasonably predict the expert release decisions. Experiments indicate that the release operation in the Oroville Lake is significantly dominated by SWP allocation amount and reservoirs with low elevation are more sensitive to inflow amount than others

Ecosystem Approach to Fisheries and Aquaculture: Implementing the FAO Code of Conduct for Responsible Fisheries

This publication provides guidance on how to implement the FAO Code of Conduct for Responsible Fisheries (CCRF) using an ecosystem approach to fisheries and aquaculture. The CCRF is a voluntary code covering all aspects of the management and development of fisheries and is designed to ensure sustainable development without adversely affecting the livelihoods of local communities that share the same resources as the fisheries. The authors outline the basic principles of the CCRF, describe concrete steps to be taken to use the ecosystem approach effectively, and recommend certain institutional changes and reforms that will be necessary if the potential of the ecosystem approach is to be realized in the Asia-Pacific region. The most significant reform needed is a paradigm shift in policy from one that is production oriented to one that is benefits oriented (social and economic). There is evidence that this is already being undertaken in the region with efforts being made to limit access, reduce the number of fishing vessels and introduce community-based rights systems. Stakeholder participation is essential and existing legal instruments and practices that interact with or impact fisheries may also need to be reconsidered, and adjustments made where necessary. In the future, it may even be necessary to regulate the inter-sectoral interactions and impacts through primary legislation. To promote broader adoption and implementation of the ecosystem approach by member countries, a wide range of regional activities is suggested by the authors including a media campaign, the building of fishery alliances among countries and capacity building in fishery agencies

The European Forest and Agriculture Optimisation Model -- EUFASOM

Land use is a key factor to social wellbeing and has become a major component in political negotiations. This paper describes the mathematical structure of the European Forest and Agricultural Sector Optimization Model. The model represents simultaneously observed resource and technological heterogeneity, global commodity markets, and multiple environmental qualities. Land scarcity and land competition between traditional agriculture, forests, nature reserves, pastures, and bioenergy plantations is explicitly captured. Environmental change, technological progress, and policies can be investigated in parallel. The model is well-suited to estimate competitive economic potentials of land based mitigation, leakage, and synergies and trade-offs between multiple environmental objectives.Land Use Change Optimization, Resource Scarcity, Market Competition, Welfare Maximization, Bottom-up Partial Equilibrium Analysis, Agricultural Externality Mitigation, Forest Dynamics, Global Change Adaptation, Environmental Policy Simulation, Integrated Assessment, Mathematical Programming, GAMS