PSO based Neural Networks vs. Traditional Statistical Models for Seasonal Time Series Forecasting

Seasonality is a distinctive characteristic which is often observed in many practical time series. Artificial Neural Networks (ANNs) are a class of promising models for efficiently recognizing and forecasting seasonal patterns. In this paper, the Particle Swarm Optimization (PSO) approach is used to enhance the forecasting strengths of feedforward ANN (FANN) as well as Elman ANN (EANN) models for seasonal data. Three widely popular versions of the basic PSO algorithm, viz. Trelea-I, Trelea-II and Clerc-Type1 are considered here. The empirical analysis is conducted on three real-world seasonal time series. Results clearly show that each version of the PSO algorithm achieves notably better forecasting accuracies than the standard Backpropagation (BP) training method for both FANN and EANN models. The neural network forecasting results are also compared with those from the three traditional statistical models, viz. Seasonal Autoregressive Integrated Moving Average (SARIMA), Holt-Winters (HW) and Support Vector Machine (SVM). The comparison demonstrates that both PSO and BP based neural networks outperform SARIMA, HW and SVM models for all three time series datasets. The forecasting performances of ANNs are further improved through combining the outputs from the three PSO based models.Comment: 4 figures, 4 tables, 31 references, conference proceeding

AN ANALYSIS OF INTERNATIONAL PRICE AND EXCHANGE RATE ELASTICITY FOR US SOYBEANS: THE CASE OF JAPAN

Stepwise model selection criteria were tested against the restrictive forms to determine the appropriate model and to confirm the law of one price for the US soybeans. Analysis shows less than one international price transmission and exchange rate elasticities in the long run indicate an incomplete exchange rate pass through.International Relations/Trade,

Measuring the Impacts of US Export Promotion Program for Wheat in Selected Importing Regions

We examine the impacts of major factors affecting the export demand of wheat with a special focus on the impacts of export promotion programs on US wheat. Study results show negative impacts of own-price and real exchange rate on export demand of wheat, while the real GDP, price of corn, and export promotion expenditure had positive and significant impacts. The per dollar returns to wheat export promotion expenditures were $1.49,$0.42, and $2.01 for Middle East, Pacific Rim, and Mexico, respectively.International Relations/Trade,

ASSESSING THE EFFICIENCY OF EXCHANGE RATE-LINKED SUBSIDIES FOR NON-PRICE EXPORT PROMOTION: THE CASE OF COTTON

Notwithstanding substantial federal financial support for the export promotion of agricultural products, ways to improve the efficiency of federal funding have not been discussed in empirical research. In this study, an equilibrium displacement framework was developed to evaluate whether the efficiency of export promotion expenditures could be increased by linking them with changes in the exchange rate. In our analysis, the gross gain to domestic cotton producers from the exchange-rate linked subsidy scheme was positive. Findings support exchange-rate linked subsidies for export promotion of agricultural products.International Relations/Trade,

NON-PRICE PROMOTION IMPACTS ON COTTON AND SOYBEANS EXPORTS UNDER EXCHANGE RATE LINKED SUBSIDIES

Issue of exchange rate-linked subsidies for non-price export promotion has recently emerged as an area of interest among marketing researchers because of fluctuating strength of US dollars and position of US agricultural goods in export markets. One solution to mitigate these impacts was to link the federal export promotion subsidies with the changing value of US dollars. In the study, an equilibrium displacement framework was developed to analyze the effectiveness of exchange rate-linked subsidies for non-price promotion by comparatively analyzing its effectiveness on US soybeans and cotton. The study result shows that an increase in promotion expenditure with an increase in the strength of US dollars and vice versa promotes the export of US cotton and soybeans in export markets and increases the efficiency of federal export promotion programs. Even though transportation cost elasticity was one of major focuses of this study, it emerged as an insignificant factor.export promotion, exchange rate linked subsidies, gross gain, and producer welfare, Agricultural and Food Policy, International Relations/Trade,

AN ANALYSIS OF COST EFFECTIVE MANAGEMENT PRACTICES TO MANAGE WATER POLLUTION PROBLEM: A CASE OF TOBESOFKEE CREEK,GEORGIA

A cost minimization model was used to find the minimum cost and environmental friendly management practices(MCEFMP). Use of MCEFMP in cattle production seems to be the most cost effective means of reducing water pollution with a marginal cost of $1200 in comparison to use of MCEFMP on other agricultural operations.Environmental Economics and Policy,

FORECASTING IRRIGATION WATER DEMAND: A STRUCTURAL AND TIME SERIES ANALYSIS

An expected utility model was developed to capture the impacts of wealth, other economic, and institutional factors on irrigation acreage allocation decisions. Predicted water demand is derived from an expected utility structural model and various ARIMA models. No significant differences arise between forecasted irrigation acreage and, thereby, amount of forecasted water demand between econometric and time series models. However, estimates of water demand differ significantly from a Blaney-Criddle-based physical model. Keywords: water forecasting, acreage response, water slippage, BC formulawater forecasting, acreage response, water slippage, BC formula, Land Economics/Use, Resource /Energy Economics and Policy,

AN ANALYSIS OF WILLINGNESS TO PARTICIPATE IN WILDERNESS OR OTHER PRIMITIVE AREAS

A logit model was used to determine the major factors explaining willingness to participate of an individual in the wilderness or other primitive area visits. The results of the study showed that education and environmental awareness were in wilderness participation decision. Demographic variables like age, race, and sex also were statistically significant and emerged as important policy variables in defining wilderness participation behavior. Characteristics of wilderness areas like crowdness, pollution, and poor management failed to produce any significant impacts in the decision making process of wilderness area visit.wilderness or other primitive area visits, policy variables, demographic characteristics, participation behavior, Consumer/Household Economics,

MACROFUNGAL DIVERSITY IN DIFFERENT VEGETATION COMPOSITIONS IN TEGHARI COMMUNITY FOREST, KAILALI, WEST NEPAL

Macrofungi are high-value forest resources that have functionally significant roles in the forest ecosystem. The macrofungal community of three different vegetation compositions, i.e., Sal (Shorea robusta) Forest, Tropical Deciduous Riverine Forest, and Tropical Evergreen Forest of Teghari Community Forest were investigated. Systematic random sampling was made where 60 plots (10 x 10 m) were laid in all different forest types (20 plots in each). A total of 102 macrofungi species were reported belonging to 36 families. Polyporaceae (17 species) was the largest family followed by Tricholomataceae (13 species) and saprophytic fungi were more frequent than mycorrhizal and parasitic fungi. The tropical evergreen forest was rich in macrofungi (59 species) followed by sal forest (40 species) and tropical deciduous riverine forest (38 species). Macrofungal diversity was directly related to surrounding host species. Similarly, increased soil moisture and canopy cover intensified the abundance of saprophytic fungi. The species richness was increased with increasing organic carbon, canopy, moisture, pH, and litter cover. However, soil nitrogen, phosphorus, and potassium were less significant in affecting species richness. Also, the disturbance was negatively correlated with the species richness of macrofungi. This study highlights the hidden diversity which is necessary for the conservation of macrofungi, to optimize forest ecosystem integrity and resilience against biotic and abiotic agent

Building Capacities for Scaling-Up Climate Smart Village in Nepal: A training manual

Globally there has been enormous effort made by thousands of organizations to promote Climate Smart Agriculture (CSA) technologies for the sake of building resilience in agriculture and farmers’ livelihood. However, the progress so far is not satisfactory. Based on the past learnings CCAFS has conceptualized the idea of Climate Smart Village (CSV) which has CSA as the major component, along with other political and socio-economic dimensions. Looking at the successful piloting of CSV, the Government of Nepal has endorsed this approach in its program. However, a mechanism to share the idea of CSV to the development bodies is lacking. Similarly, the extension workers and other staffs of local governments do not have enough procedural understanding. Therefore, to scale-up CSV approach in Nepal, capacity building of government staffs and local leaders, especially at local and provincial level, is an absolute necessity. A guide book could be the means to facilitate the process of such capacity building. Hence this manual is developed as a guide book for organizing capacity building trainings to the government and non-government development professionals. It will also serve as a resource book to help development workers from local and provincial governments, local leaders, policy makers, researchers, and academicians to understand more about the idea and approach of CSV. Ultimately, this publication is expected to contribute to the mission of scaling-up the CSV approach for the enhanced resilience of farming communities in Nepal and around the world