Q-Learning Induced Artificial Bee Colony for Noisy Optimization

The paper proposes a novel approach to adaptive selection of sample size for a trial solution of an evolutionary algorithm when noise of unknown distribution contaminates the objective surface. The sample size of a solution here is adapted based on the noisy fitness profile in the local surrounding of the given solution. The fitness estimate and the fitness variance of a sub-population surrounding the given solution are jointly used to signify the degree of noise contamination in its local neighborhood (LN). The adaptation of sample size based on the characteristics of the fitness landscape in the LN of a solution is realized here with the temporal difference Q-learning (TDQL). The merit of the present work lies in utilizing the reward-penalty based reinforcement learning mechanism of TDQL for sample size adaptation. This sidesteps the prerequisite setting of any specific functional form of relationship between the sample size requirement of a solution and the noisy fitness profile in its LN. Experiments undertaken reveal that the proposed algorithms, realized with artificial bee colony, significantly outperform the existing counterparts and the state-of-the-art algorithms

Migration in Multi-Population Differential Evolution for Many Objective Optimization

The paper proposes a novel extension of many objective optimization using differential evolution (MaODE). MaODE solves a many objective optimization (MaOO) problem by parallel optimization of individual objectives. MaODE involves N populations, each created for an objective to be optimized using MaODE. The only mode of knowledge transfer among populations in MaODE is the modified version of mutation policy of DE, where every member of the population during mutation is influenced by the best members of all the populations under consideration. The present work aims at further increasing the communication between the members of the population by communicating between a superior and an inferior population, using a novel migration strategy. The proposed migration policy enables poor members of an inferior population to evolve with a superior population. Simultaneously, members from the superior population are also transferred to the inferior one to help it improving its performance. Experiments undertaken reveal that the proposed extended version of MaODE significantly outperforms its counterpart and the state-of-the-art techniques

Evolution of an atmospheric boundary layer at a tropical semi-arid station, Anand during boreal summer month of May - A case study

The evolution of an Atmospheric Boundary Layer (ABL) over a semi-arid land station, Anand, (22°35â²N, 72°55â²E, 45.1 m asl) in India, during the summer month of May, is examined using surface meteorological and radiosonde temperature and humidity data collected during LASPEX-97 for a 5-day period from 13-17 May 1997. These 5 days remained undisturbed, and clear sky weather conditions prevailed. However, the data obtained on these days are helpful in understanding the diurnal variation of the ABL over a land station. There are 5 observations per day at an interval of 3 h beginning with 0530 IST. The 0530 IST ascents are chosen to find out the initial ABL heights which exhibit the nocturnal cooling conditions. It is observed from the analysis of θv, θe, θes, q, and P profiles that the nocturnal boundary layer is stable with an inversion close to the ground. The top of an inversion layer is characterized by a θe minimum and a θes maximum. After dawn, the ABL grows to a height of 827 m at 0830 IST. Aloft, a residual layer up to 3200 m is observed. The daytime strong insolation causes formation of an unstable boundary layer close to the ground at 1130 IST with an elevated stable layer between 550 and 930 m. It is only by 1430 IST that the stable layer gets completely wiped out and a convective mixed layer develops up to a height of 3280 m. Lack of moisture inhibits formation of clouds. Hence the ABL at a semi-arid station like Anand is stable in the morning with residual layer aloft and develops into a dry convective boundary layer in the afternoon and evening. Growth of the convective boundary layer (CBL) is observed to be very rapid as it reaches a height up to 3280 m by the afternoon

Vermicomposting of green Eucalyptus leaf litter by Eisenia foetida and Eudrilus eugenia

Effective clearance of different types of waste has become significant to sustain healthy environment. Vermicomposting has become a suitable substitute for the safe, hygienic and cost effective disposal of organic solid wastes. Earthworms decompose organic waste leading to the production of compost which is high in nutrient content. The present work has been designed to reveal competitive and / or beneficial interactions by studying the inter-specific interactions in terms of growth, maturation, survival and vermicomposting efficiency of two earthworm species Eisenia foetida and Eudrilus eugenia exposed to green leaf litter of Eucalyptus and measured physical variables during entire process. The complete process was taken fourteen weeks.Work was done in plastic beans in four set. 100 % cattle dung was also taken as a control. During the process following parameters viz. pH, temperature, biomass reduction and moisture content were analysed.pHof vermicomposting substrate was recorded low initially acidic but at last stage set in alkaline range. In case of temperature, it was changed 16-18°C ± 1°C from initial value. This was higher than control cattle dung (13°C± 1°C). Organic biomass was also depleted during process which was about 70-71 % ±1 % from initial level as compaired to cattle dung (46 %). Moisture content was lowerinitially then increased and set at high level

Effect of sowing dates and varieties on soybean performance in Vidarbha region of Maharashtra, India

oybean production is widely fluctuating in response to agro-environmental conditions year to year in Vidarbha region. Weather variations are the major determinants of soybean growth and yield. It is also important to study the response of suitable soybean varieties to varying weather parameters. So a field investigation was carried out to study the crop weather relationship of soybean and to optimize the sowing date with different soybean varie-ties. The results revealed that soybean crop sown up to 27th MW accumulated higher growing degree days (1640.5 0C day), photothermal units (20498.1 0C day hour) and recorded significantly higher seed yield (839 kg ha-1) and biological yield (2773 kg ha-1) with maximum heat use efficiency (0.51 kg ha-1°C day-1) and water productivity (2.49 kg ha-mm-1). Later sowings i.e. 30th MW sowing caused decreased amount of rainfall and increased maximum temperature regime across the total growing period with consequently lower seed yield (530 kg ha-1), GDD (1539.2 0C day), PTU (18689.9 0C day hour), heat use efficiency (0.34kg ha-1 °Cday-1) and water productivity (2.05kg ha-mm-1). Soybean variety TAMS 98-21 recorded significantly higher seed yield (734 kg ha-1) and highest biological yield (2649 kg ha-1) with maximum heat use efficiency (0.44 kg ha-1 °C day-1), GDD (1650.5 0C day ) and water productivity (2.41 kg ha-mm-1). Thus, the results of this study illustrated the importance of early sowing with suitable variety of soybean and indicates that sowing upto 27th MW with variety TAMS 98-21 is optimum for maximizing the yield in the Akola region of Vidarbha

Probability distribution of residence-times of grains in sandpile models

We show that the probability distribution of the residence-times of sand grains in sandpile models, in the scaling limit, can be expressed in terms of the survival probability of a single diffusing particle in a medium with absorbing boundaries and space-dependent jump rates. The scaling function for the probability distribution of residence times is non-universal, and depends on the probability distribution according to which grains are added at different sites. We determine this function exactly for the 1-dimensional sandpile when grains are added randomly only at the ends. For sandpiles with grains are added everywhere with equal probability, in any dimension and of arbitrary shape, we prove that, in the scaling limit, the probability that the residence time greater than t is exp(-t/M), where M is the average mass of the pile in the steady state. We also study finite-size corrections to this function.Comment: 8 pages, 5 figures, extra file delete

Reduced Hamiltonian for next-to-leading order Spin-Squared Dynamics of General Compact Binaries

Within the post Newtonian framework the fully reduced Hamiltonian (i.e., with eliminated spin supplementary condition) for the next-to-leading order spin-squared dynamics of general compact binaries is presented. The Hamiltonian is applicable to the spin dynamics of all kinds of binaries with self-gravitating components like black holes and/or neutron stars taking into account spin-induced quadrupolar deformation effects in second post-Newtonian order perturbation theory of Einstein's field equations. The corresponding equations of motion for spin, position and momentum variables are given in terms of canonical Poisson brackets. Comparison with a nonreduced potential calculated within the Effective Field Theory approach is made.Comment: 11 pages, minor changes to match published version at CQ

Strong clustering of non-interacting, passive sliders driven by a Kardar-Parisi-Zhang surface

We study the clustering of passive, non-interacting particles moving under the influence of a fluctuating field and random noise, in one dimension. The fluctuating field in our case is provided by a surface governed by the Kardar-Parisi-Zhang (KPZ) equation and the sliding particles follow the local surface slope. As the KPZ equation can be mapped to the noisy Burgers equation, the problem translates to that of passive scalars in a Burgers fluid. We study the case of particles moving in the same direction as the surface, equivalent to advection in fluid language. Monte-Carlo simulations on a discrete lattice model reveal extreme clustering of the passive particles. The resulting Strong Clustering State is defined using the scaling properties of the two point density-density correlation function. Our simulations show that the state is robust against changing the ratio of update speeds of the surface and particles. In the equilibrium limit of a stationary surface and finite noise, one obtains the Sinai model for random walkers on a random landscape. In this limit, we obtain analytic results which allow closed form expressions to be found for the quantities of interest. Surprisingly, these results for the equilibrium problem show good agreement with the results in the non-equilibrium regime.Comment: 14 pages, 9 figure