Abstract: The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.
Abstract: Renewable water resources are crucial production
variables in arid and semi-arid regions where intensive agriculture is
practiced to meet ever-increasing demand for food and fiber. This is
crucial for the Dez and Moghan command areas where water delivery
problems and adverse environmental issues are widespread. This
paper aims to identify major problems areas using on-farm surveys of
200 farmers, agricultural extensionists and water suppliers which was
complemented by secondary data and field observations during 2010-
2011 cultivating season. The SPSS package was used to analyze and
synthesis data. Results indicated inappropriate canal operations in
both schemes, though there was no unanimity about the underlying
causes. Inequitable and inflexible distribution was found to be rooted
in deficient hydraulic structures particularly in the main and
secondary canals. The inadequacy and inflexibility of water
scheduling regime was the underlying causes of recurring pest and
disease spread which often led to the decline of crop yield and
quality, although these were not disputed, the water suppliers were
not prepared to link with the deficiencies in the operation of the main
and secondary canals. They rather attributed these to the prevailing
salinity; alkalinity, water table fluctuations and leaching of the
valuable agro-chemical inputs from the plants- route zone with farreaching
consequences. Examples of these include the pollution of
ground and surface resources due to over-irrigation at the farm level
which falls under the growers- own responsibility. Poor irrigation
efficiency and adverse environmental problems were attributed to
deficient and outdated farming practices that were in turn rooted in
poor extension programs and irrational water charges.