Fuzzy logic approach in prioritization of crop growing parameters in protected farms: a case in North East India

 Global food demand is rising exponentially as the population is increasing.  Protected farming is becoming increasingly popular among the farming communities for fast growing vine crops round the year.  Consideration of crop growing parameters while designing and maintaining a protected farm is very important for optimal crop growth and profit.  Many farmers does not consider all the crop growing parameters and does not know the importance of all factors in the optimal crop growth.  In this paper, an attempt has been made to prioritize 12 crops growing parameters using fuzzy approach.  12 crop growing parameters were selected from the literature and scored by four different evaluation methods viz., food consumer importance, expert’s importance, farmer importance and food dealer importance.  The results revealed that the descending order of relative importance of the 12 crop factors are water quality, light intensity, nutrient availability, crop cultivar, substrate media, daylight length, moisture availability, crop spacing, temperature, air freshness, air circulation and relative humidity respectively.  Priority for crop growing factors must be considered while designing and maintaining a protected farm for optimal crop growth and net return

Prediction of Wave Energy Potential in India: A Fuzzy-ANN Approach

The conversion efficiency of wave energy converters is not only unsatisfactory but also expensive, which is why the popularity of wave energy as an alternative to conventional energy sources is subjacent. This means that besides wave height and period, there are many other factors which influence the amount of “utilizable” wave energy potential. The present study attempts to identify these important factors and predict power potential as a function of these factors. Accordingly, a polynomial neural network was utilized, and fuzzy logic was applied to identify the most important factors. According to the results, wave height was found to have the maximum importance followed by wave period, water depth, and salinity. In total, 12 different neural network models were developed to predict the same output, among which the model with all of the 4 inputs was found to have optimal performance

Suitable Substrate for Crop Growth under Protected Farms – An Assessment

With the advent of civilization, open field agriculture is facing some major challenges; most importantly decrease in per capita land availability. In this paper, an attempt has been made to review crop growing substrates for protected farms. Substrate selection is a critical factor for optimal production of high-quality vegetables. Rooting depth determines the volume of substrate from. Consideration of optimal crop growing substrate and irrigation method while designing and maintaining a protected farm is very important for optimal crop growth and profit. Most farmers do not consider all the crop growing parameters for the optimal crop growth. &nbsp

Economic of cubical and semi-spherical shape stacked protected farms for marginal farmers

As the populating is increasing, the average land holding capacity is shrinking. Larger machineries are uneconomical in small and marginal lands. An attempt has been made in this paper for review of gravity drip irrigation system in a 3-layered stacked protected farm with. Gravity drip irrigation is a low tech and cheap irrigation system to provide water judiciously in protected farms for growing vegetable under limited land availability. The system does not require any external power for operation. The approximate construction cost of a 3-layered stacked protected farm of 6m height on land 10m length and 10m width is $ 2700. The average crops yield from a three-layer sacks protected farm on 10m x 10m area for spinach, tomato, pepper, cucumber and potato are 0.35, 1.55, 1.35, 1 and 1.5 ton respectively

Application of DEMATEL-TOPSIS Method to Analyze Operational Efficiency of Hydropower Plants

The ever-growing demand for luxury has increased the stress on conventional energy sources and encourages scientists and engineers to look for alternatives. Hydropower is by far the most inexpensive but reliable source of energy which is deemed to have the capacity to substitute for conventional energy sources. The worldwide contribution of hydropower plants (HPP) in supplying the demand for electricity is 1106 TWh. The problem with hydropower lies with the fact that its efficiency depends on multiple factors which are a function of climatic, hydraulic and socio-economic parameters. All these parameters again depend upon hydraulic loss imposed due to time in use, change in energy requirements, locational interference and quality of the machine installed. As there are multiple parameters having different levels of influence on the performance efficiency of HPP. Thus some factors are overrated and some others remain under rated which results in erroneous decision-making. The present study proposes a new hybrid model based on Decision-Making Trial and Evaluation Laboratory (DEMATEL) with Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The priorities are determined by hybrid method namely DEMATEL- TOPSIS. According to the results, efficiency of generator is most significant for efficiency of HPP

Evaluation of Hydropower Plants with respect to Cost Incurred by Fuzzy Decision Making

 Hydropower projects are one of the most inexpensive and reliable renewable energy alternatives which can substitute conventional energy sources. As cost benefit analysis of a project represent its performance or viability the financial implication of a project is needed to be evaluated. The present study applied a cognitive method of decision making to rate different hydro-power projects, based on their financial liabilities. The projects were evaluated based on the cost incurred during the installation and operation phase. This decision making will help to identify a method for rating hydro power plants or proposed plants in terms of financial requirements. The method was developed in such a manner that the decision made from the result of the new method will be completely objective and free from emotional influence.          

Prediction of Performance under uncertainty by Water Treatment Plants: A MCDM-ANN Approach

The Water Treatment Plants (WTP) ascertains supply of potable water for consumption in different types of industrial, agricultural and domestic units. The functionality of WTP is responsible for sustaining the condition of public health specifically for urban based units. It indicates that all the methods assign equal importance to each of the variables. That’s why procedures lack the ability to adapt with situations. In this aspect, the present investigation utilized MCDM and ANN in a cascaded framework to assess the plant performance based on Removal Efficiency, Energy Required, Operation and Maintenance Cost and Impact on Environment.The current research is an endeavour to implement the factors in amalgamation so that an extensive envision of the plant performance can be concluded. The new method is used to estimate the performance of WTP under 20 likely and unlikely scenarios. Model results were compared with the evaluation results from "Removal Efficiency" method and were found to have sufficient coherency