Assessment of Sustainable Development

The objective of this paper is to introduce fuzzy set theory and develop fuzzy mathematical models to assess sustainable development based on context-dependent economic, ecological, and societal sustainability indicators. Membership functions are at the core of fuzzy models, and define the degree to which indicators contribute to development. Although a decision-making process regarding sustainable development is subjective, fuzzy set theory links human expectations about development, expressed in linguistic propositions, to numerical data, expressed in measurements of sustainability indicators. In the future, practical implementation of such models will be based on elicitation of expert knowledge to construct a membership function. The fuzzy models developed in this paper provide a novel approach to support decisions regarding sustainable development.agriculture;assessment;fuzzy set theory;sustainable development

GIS-fuzzy logic approach for building indices: regional feasibility and natural potential of ranching in tropical wetland

The regional feasibility of ranching (RFR) index was obtained in order to evaluate the productive potential of farms in the Pantanal. Five indicators were selected by expert and employed for the developing of the index. One of the five indicators corresponded to the natural potential for livestock ranching (NPLR) index which was generated by GIS-fuzzy logic. Fuzzy inference process, involving definitions of membership functions, fuzzy set operations and inference rules was implemented and validated with the participation of primary stakeholders. Different scenarios were simulated in a batch, next validated and adjusted with the participation of stakeholders. Both procedures were performed by the use of the Webfuzzy software. The NPLR and RFR index values, calculated for the pilot ranch, corresponded to the expectations of both expert and stakeholders. Fuzzy logic combined with landscape metric seems to be suitable for the definition of the productive natural potential of ranches to produce livestock in the Pantanal. The indices can assess the regional feasibility of ranching, contributing to decision-making of stakeholders.\u

CAP-reform and the provision of non-commodity outputs in Brandenburg

This paper presents an attempt to model the response of selected farms to decoupled direct payments and the associated impact on the provision of a defined set of non-commodity outputs (NCO’s) using a combined modelling approach consisting of the AgriPoliS and MODAM models. AgriPoliS focuses on the socio-economic dimension of multifunctionality at the individual farm and regional levels and explicitly models heterogeneous farms (in size, location and efficiency) within a competitive and dynamic environment. The linear-programming model MODAM allows a detailed representation of production processes and their impact on the environmental dimension of multifunctionality at the farm level. We simulate the impact of a uniform area payment and a fully decoupled single farm payment. Our case study region is the district Ostprignitz-Ruppin in Brandenburg. Results show that the decoupling schemes create a trade-off between the NCO’s and that adjustment reactions differ between farms depending on their legal form, size, and production.decoupling, multifunctionality, non-commodity outputs, modelling, simulation, policy analysis, ecological indicators, Agricultural and Food Policy, Land Economics/Use,

Integrating remote sensing, geographic information system and fuzzy logic: an index to evaluate the natural potential for livestock ranching in the Pantanal.

Abstract: In this study, an index natural potential for livestock ranching (NPLR) at ranch level in the Pantanal wetland was obtained using landscape indicators combined with fuzzy inference process. Four landscape indicators related with livestock production were selected by an expertise group. The application of this approach was illustrated through a pilot ranch located in the Nhecolândia sub-region, Pantanal, MS. Remote Sensing (RS) and Geographic Information System (GIS) technologies were used to map the vegetation types and aquatic habitats (landscapes types) in this ranch. Landscape type?s composition metrics were obtained using the ArcGis 9 and were used to estimate the four indicators selected by expertise: forest cover proportion (FC); landscape productive value (LPV); diversity of aquatic habitats (DAH) and flooding degree (FD). Fuzzy inference process involving definitions of membership functions, fuzzy set operations and inference rule were run and validated with the participation of core stakeholders. Different scenarios also were simulated in batch and validated with the participation of stakeholders. Both procedures were performed by Webfuzzy software. The NPLR index value found in the pilot ranch was as expected by both expertise and stakeholders. Fuzzy logic combined with landscape metric seems to be suitable for the definition of the natural potential of ranches to produce livestock in the Pantanal.Geopantanal 2012

Expert System Development for the Prevention of Hoof Pathologies Applied to the Intensive Swine Production

Claw lameness can be associated with biomechanical factors caused by imbalances of the pressure distribution under the hooves when swine are confined in modern facilities with hard concrete flooring. Comparing hoof pressure distribution data of swine boars walking over two different types of floors (standard concrete vs. 3mm rubber mattress) in previous research, it was found a great advantage favoring the rubber mat flooring showing that it was capable of reducing pressures under the claws as the pressure became more evenly distributed under this treatment resulting in balanced weight-bearing surfaces. The objective of this study was to develop an expert system based on Fuzzy logic algorithm for the prevention of hoof pathologies applied to the intensive swine production by estimating occurrence of claw lesions based on the association of knowledge gathered on pressure distribution from previous research as well as the influences of nutrition, friction coefficients found on different types of available flooring, hoof sizes and animal weight on the welfare of the swine’s locomotory system. The data were correlated initially using Matlab® platform associating expert’s knowledge and literature through a knowledge system that weights the variables according to their impact on claw health. The final user interface was coded using Microsoft Visual Studio Rapid Application Development tool and the resulting system was validated in several different laboratory scenarios and its performance was considered to be satisfactory according to findings in the literature. The expert system was coded and the authors concluded that the system could be a great contribution and advance in the swine’s industry, nonetheless, its performance still requires field testing for fine adjustments which should be encouraged to be carried out in further researches

Decision support systems for large dam planning and operation in Africa

Decision support systems/ Dams/ Planning/ Operations/ Social impact/ Environmental effects

Assessment of Sustainable Development

The objective of this paper is to introduce fuzzy set theory and develop fuzzy mathematical models to assess sustainable development based on context-dependent economic, ecological, and societal sustainability indicators. Membership functions are at the core of fuzzy models, and define the degree to which indicators contribute to development. Although a decision-making process regarding sustainable development is subjective, fuzzy set theory links human expectations about development, expressed in linguistic propositions, to numerical data, expressed in measurements of sustainability indicators. In the future, practical implementation of such models will be based on elicitation of expert knowledge to construct a membership function. The fuzzy models developed in this paper provide a novel approach to support decisions regarding sustainable development

DIAGNOSIS GEJALA PENYAKIT TUBERKULOSIS MENGGUNAKAN FUZZY EXPERT SYSTEM BERBASIS WEB

Tuberkulosis (TB) adalah salah satu penyakit yang menyebabkan kematian tinggi pada manusia. Pencegahan penyakit ini telah dicari oleh para profesional medis dan peneliti. Sayangnya, penanganan TB masih dilakukan secara manual dan sangat tergantung pada ahli medis yang jumlahnya terbatas, sehingga dalam penelitian ini dilakukan pengembangan sistem informasi alternatif untuk mengatasi masalah tersebut. Sistem diagnosis gejala TB ini dikembangkan menggunakan metode sistem pakar fuzzy. Data masukan pada sistem ini adalah gejala yang diderita penderita, yang terdiri dari batuk, penurunan berat badan, sesak napas, kehilangan nafsu makan, demam, berkeringat di malam hari, dan malaise. Prosesnya dimulai dari memasukkan data gejala, kemudian diproses menggunakanfuzzy yang terdiri dari proses fuzifikasi, inferensi dan defuzifikasi.Aturan penyakit diberikan oleh para ahli yang ahli di bidangnya dan dari sumber jurnal. Keluaran dari sistem menampilkan antarmuka diagnosis penyakit di web. Hasil penelitian ini adalah sistem informasi yang dapat memberikan hasil diagnosis penyakit kepada pengguna. Perhitungan nilai akurasi juga dilakukan untuk mengetahui seberapa akurat fuzzy dalam sistem ini, dan dari hasil perhitungan ditemukan bahwa nilai akurasi yang didapat adalah sebesar 82% yang menunjukkan bahwa logika fuzzy baik untuk proses diagnosis. Kata kunci — TB, pakar, sistem pakar fuzzy, logika fuzzy, diagnosis Tuberculosis (TB) is one of the diseases that causes high mortality in humans. The prevention of this disease has been sought by medical professionals and researchers. Unfortunately, the handling of TB is still manual and very dependent on medical experts who are very limited in number. In this study we propose an alternative information technology to overcome this problem. To overcome this problem a TB diagnostic system is developed using a fuzzy expert system. Input data on this system are the symptoms suffered by the sufferer, which consists of cough, weight loss, breathless, loss of appetite, fever, sweat at night, and malaise. The input data is then processed using fuzzy logic which consists of a process of fuzification, inference and defuzification. The output of the system displays the disease diagnosis interface on the web. Disease rules are given by experts who are experts in their fields and from journal sources. The results of the study are information systems that can provide the results of disease diagnosis to the user. The calculation of the accuracy value is also done to find out how accurate the fuzzy logic is in this system, and from the results of these calculations it is found that the accuracy value is 82% which shows that fuzzy logic is good for the diagnostic process. Keywords—tuberculosis, expert, fuzzy expert system, fuzzy logic, diagnosi